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NEUROMODULATION SYMPOSIUM

MINNESOTA

APRIL 14 - 15, 2016THE COMMONS HOTEL

MINNEAPOLIS, MN

neuromodulation.umn.edu

Dear Colleagues,

Welcome to the 4th Annual Minnesota Neuromodulation Symposium.

Neuromodulation is a rapidly-growing field, encompassing a wide spectrum of implantable and non-invasive technology-based approaches for the treatment of neurological and psychiatric disorders. It represents an important research nexus of basic and clinical neu-roscience, and of engineering sciences. It also represents an important industrial sector in the medical device industry with products already benefiting a number of patients. A collaborative effort by all stakeholders will be needed to further expedite the process of translating basic research discoveries into applied and clinical research, industrial research and development, and even manufacturing, which will result in a more immediate impact to healthcare.

This symposium is aimed at bringing together basic scientists, engineers, clinicians, industrial practitioners, entrepreneurs, and policy makers to discuss challenges and opportunities in neuromodulation and neurotechnology. Advancing the field of neuromodulation represents challenges to developing engineering methodologies, understanding mechanisms of neuromodulation at cellular and system levels, translating research to treat patients, and closely integrating the regulatory process within the research and clinical environment. We are very pleased to address these challenges through our outstanding line-up of invited speakers that represent thought leaders from academia, industry, and government, whom over the next two days will review significant progress in neuromodulation and neurotechnology, providing a glimpse into the future of this fascinating field. We are also very pleased that the symposium has attracted a record number of scientific contributions from many institutions to be presented in the Poster Session. With close to 100 abstracts representing 37 different institutions, 18 non-profit organizations, 10 corporations and 12 countries, we are expecting a wonderful meeting and we anticipate warm and vivid discussions.

I would like to take this opportunity to thank many colleagues for their great contributions and efforts, to invited speakers and panelists for sharing their visions, to poster and oral presenters for presenting original works, to members of the organizing committee for their great efforts throughout the process, to members of the international program committee for promoting the symposium, to judges who volunteered their time and expertise, and to IEM staff for their tireless efforts. We are also very grateful to our co-sponsors whose support are essential for a successful meeting.

I hope that you will find the symposium to be stimulating, productive, and enjoyable.

Kind regards,

Bin He, Ph.D. Symposium Chair

ContentsGeneral Information 2Agenda: Day 1 3Agenda: Day 2 4Sponsors 5Speakers 7Selected Highlight Talks 12Posters 13Abstracts 21Notes 123Committees 124

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THE COMMONS HOTEL615 Washington Ave SE, Minneapolis, MN 55414

2

GENERAL INFORMATION

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AGENDA: DAY 1Welcome RemarksBin He, PhDSymposium Chair

2:00pm - 2:05pm

Plenary Lecture: Closing the DBS Loop in Parkinson’s Disease: The Promise and the Pitfalls Peter Brown, MD Professor of Experimental Neurology Director of the Medical Research Council Brain Network Dynamics Unit University of Oxford Moderator: Bin He, PhD (UMN)

Plenary Lecture: Chronic Ambulatory Brain Recording Using Totally Implanted Devices: Next Steps in Development Philip A. Starr, MD, PhD Professor of Neurological Surgery Dolores Cakebread Endowed Chair University of California, San Francisco Moderator: Jerry Vitek, MD, PhD (UMN)

Invited Talk: Changing the Culture of Neuromodulation Research through the NIH SPARC and BRAIN InitiativesGrace Peng, PhD Program Director Division of Discovery Science & Technology (DDST) National Institute of Biomedical Imaging and Bioengineering (NIBIB) National Institutes of Health (NIH) Moderator: Kip Ludwig, PhD (Mayo Clinic)

Invited Talk: A FDA Staff Perspective on the Regulatory Landscape for Neurotechnologies and Medical Device Readiness Carlos Peña, PhD Director Division of Neurological and Physical Medicine Devices Office of Device Evaluation Center for Devices and Radiological Health Food and Drug Administration (FDA) Moderator: Kelvin Lim, MD (UMN)

Break

Highlights in Neuromodulation I This session consists of brief highlight talks of poster presentations.Moderator: Hubert Lim, PhD (UMN)MNS197: Cortical Implantation of a 16-channel Wireless Floating Microelectrode Array (WFMA) Stimulator.Philip Troyk, Illinois Institute of TechnologyMNS160: Cortical Sensing and Wearable Closed-loop DBS in an Essential Tremor PatientJeffrey Herron, University of Washington, SeattleMNS146: Closed-loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms — Is Beta Enough?Luke Johnson, UMNMNS111: Dopamine Release in the Nonhuman Primate Caudate and Putamen Depends upon Site of Stimulation in the Subthalamic NucleusPaul Min, Mayo Clinic, RochesterMNS101: Interrogating Neural Circuitry Underlying Neuroeconomic Decision-making in Mouse Models of Addiction: A Functional Approach to Translation.Brian Sweis, UMN

Panel Discussion – Invasive Neuromodulation: Challenges & TrendsModerator: Jerry Vitek, MD, PhD (UMN) Panelists: Peter Brown (University of Oxford) Stephen Carcieri (Boston Scientific) Steve Goetz (Medtronic) DeLea Peichel (St. Jude Medical) Carlos Peña (FDA) Grace Peng (NIH) Philip A. Starr (University of California, San Francisco)

Reception

2:05pm - 2:40pm

2:40pm - 3:15pm

3:15pm - 3:40pm

3:40pm -4:10pm

4:10pm - 4:35pm

4:35pm - 5:00pm

5:00pm - 6:10pm

6:10pm - 8:00pm

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AGENDA: DAY 2Networking Breakfast8:00am - 8:30am

Plenary Lecture: Perturbation-based Translatable Physiologic Biomarkers Alvaro Pascual-Leone, MD, PhD Professor of Neurology, Harvard Medical School Director, Berenson-Allen Center for Noninvasive Brain Stimulation at Beth Israel Deaconess Medical Center Moderator: James Carey, PhD, PT, FAPTA (UMN)

Plenary Lecture: The Importance of Point Process Models to Quantify the Electroencephalogram Jose C. Principe, PhD Distinguished Professor of Electrical and Computer Engineering BellSouth Professor University of Florida Vice President for Technical Activities IEEE Engineering in Medicine and Biology Society Moderator: Phil Troyk, PhD (Illinois Institute of Technology)

Neuromodulation Research at UMNBin He, PhD Director, Institute for Engineering in Medicine Director, Center for Neuroengineering Medtronic-Bakken Endowed Chair for Engineering in Medicine Distinguished McKnight University Professor of Biomedical Engineering Moderator: Tim Ebner, MD, PhD (UMN)

Invited Talk: Brain-Machine Interfaces Beyond Neuroprosthetics: Controlling Neural Circuits, Restoring Function and Changing the Way We Think Karen Moxon, PhD Professor, Associate Dean for Research, School of Biomedical Engineering Science and Health Systems Drexel University Moderator: David Redish, PhD (UMN)

Poster Session

Highlights in Neuromodulation IIThis session consists of brief highlight talks of poster presentations.Moderator: Tim Ebner, MD, PhD (UMN)MNS124: Implanted Brain Computer Interface for Real-time Cortical Control of Hand Movements in a Human with QuadriplegiaGaurav Sharma, Battelle Memorial InstituteMNS141: Safe Direct Current Stimulation for the Treatment of Chronic Peripheral PainGene Fridman, Johns Hopkins UniversityMNS192: Controlling Plasticity in Sensory Cortical Regions Using Multisensory NeuromodulationCory Gloeckner, UMNMNS205: Investigating TMS-evoked Cortical Responses with EEG in Chronic Stroke Whitney Gray, Emory UniversityMNS145: Improving Motor Recovery after Stroke by Combined rTMS and BCI TrainingNessa Johnson, UMN

Panel Discussion – Neuromodulation and Neural Interfacing: Present and FutureModerator: Bin He, PhD (UMN) Panelists: Tim Denison (Medtronic) Hubert Lim (UMN) Karen Moxon (Drexel University) Alvaro Pascual-Leone (Harvard Medical School) Jose C. Principe (University of Florida) Nitish V. Thakor (Johns Hopkins University)

Closing Ceremony – Announcement of Poster Awards

8:30am - 9:05am

9:05am - 9:40am

9:40am - 10:05am

10:05am - 10:30am

10:30am - 12:30pm

12:00pm - 1:00pm

1:00pm - 1:35pm

3:10pm - 3:30pm

Plenary Lecture: Neurotechnologies for Peripheral and Visceral Neuromodulation Nitish V. Thakor, PhD Professor of Biomedical Eng, Electrical Eng, Neurology Director, Neuroengineering Training Program Johns Hopkins University Editor in Chief, Medical and Biological Engineering and Computing Moderator: Tim Denison, PhD (Medtronic)

Lunch

1:35pm - 2:00pm

2:00pm - 3:10pm

ORGANIZED AND SPONSORED BY

PLATINUM SPONSORS

PREMIERE SPONSORS

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SPONSORS

GOLD SPONSORS

MAROON SPONSORS

TECHNICAL Co-SPONSORS

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SPONSORS

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SPEAKERSPeter Brown, MDProfessor of Experimental NeurologyDirector of the Medical Research Council Brain Network Dynamics UnitUniversity of Oxford

Peter Brown is Director of the MRC Brain Network Dynamics Unit at the University of Oxford. The Unit’s goal is to understand and exploit the moment-to-moment interactions between nerve cells that are critical for brain functions, with a special focus on developing novel therapies to specifically target the disturbed circuit interactions arising in disease. Peter Brown is also Professor of Experimental Neurology at the University of Oxford, a practicing Consultant Neurologist at Oxford University Hospitals Trust, and a Nicholas Kurti Senior Research Fellow at Brasenose College, Oxford. Up until 2010 he was a Professor of Neurology at University College London, where he was also head of the Sobell Department of Motor Neurosciences and Movement Disorders and a Consultant Neurologist at the National Hospital for Neurology & Neurosurgery.

Currently Professor Brown leads a multidisciplinary group of clinicians, bioengineers and psychologists interested in normal and abnormal motor control. He has demonstrated the importance of abnormal neural synchronisation in patients with Parkinson’s disease and pioneered closed-loop deep brain stimulation in this condition.

Bin He, PhDDirector, Institute for Engineering in Medicine Director, Center for Neuroengineering Medtronic-Bakken Endowed Chair for Engineering in Medicine Distinguished McKnight University Professor of Biomedical Engineering

Bin He is a Distinguished McKnight University Professor of Biomedical Engineering, Medtronic-Bakken Endowed Chair for Engineering in Medicine, Director of the Institute for Engineering in Medicine, Director of the Center for Neuroengineering, and Director of the NSF IGERT Neuroengineering Training Program at the University of Minnesota. Dr. He’s research interests cover a broad spectrum in biomedical engineering, mainly in neuroengineering and biomedical imaging. He has made significant original contributions to electrophysiological source imaging, multimodal neuroimaging, and brain-computer interface. He has published over 200 peer reviewed journal articles and is the sole editor of the text book entitled Neural Engineering (2nd Ed, 2013, Springer). Dr. He is a recipient of the Academic Career Achievement Award from the IEEE Engineering in Medicine and Biology Society (EMBS), the Outstanding Research Award from the International Federation of Clinical Neurophysiology, the Established Investigator Award from the American Heart Association, among others. A Fellow of International Academy of Medical and Biological Engineering, IEEE, American Institute of Medical and Biological Engineering and Institute of Physics, Dr. He served as a Past President of IEEE EMBS, International Society for Functional Source Imaging, and International Society for Bioelectromagnetism. Dr. He is the Editor-in-Chief of IEEE Transactions on Biomedical Engineering, and is a member of the NIH BRAIN Multi-council Working Group.

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SPEAKERSKaren Moxon, PhDProfessor, Associate Dean for Research, School of Biomedical Engineering Science and Health Systems Drexel University

Karen Moxon is a Professor and Associate Dean for Research in the School of Biomedical Engineering, Science and Health Systems at Drexel University. Her work focuses on how neurons represent sensorimotor information and the development of brain-machine interface (BMI) technology for restoration of function after spinal cord injury. Early in her career, Dr. Moxon worked on the first demonstration of BMI technology (Chapin, Moxon et al., 1999) to control a robotic arm to replace forelimb function. She also developed novel neural interface devices to improve the longevity of microelectrodes establishing ceramic as an ideal insulator for chronic, thin-film microelectrodes that has been adopted by many labs and the use of porous silicon in the development of thin-film microelectrodes to deliver neuroprotective drugs, minimizing damage from insertion. Her lab developed the first BMI for restoration of hindlimb function after complete spinal transection. This experimental paradigm is being used to study neuronal plasticity in supraspinal networks and its role in functional recovery. Most recently, she developed a closed loop BMI system that decodes commands for volitional control of movement and uses those commands to control stimulation in the spinal cord to restore function after paraplegia.

Alvaro Pascual-Leone, MD, PhDProfessor of Neurology, Harvard Medical School Director, Berenson-Allen Center for Noninvasive Brain Stimulation at Beth Israel Deaconess Medical Center

Alvaro Pascual-Leone, MD, PhD, is Professor of Neurology at Harvard Medical School, Chief for the Division of Cognitive Neurology, Director of the Berenson-Allen Center for Noninvasive Brain Stimulation, and a practicing cognitive neurologist at Beth Israel Deaconess Medical Center. His research aims at understanding the mechanisms that control brain plasticity across the life span to be able to modify them for the patient’s optimal behavioral outcome, prevent age-related cognitive decline, reduce the risk for dementia, and minimize the impact of neurodevelopmental disorders. Dr. Pascual-Leone is a world leader in the field of noninvasive brain stimulation where his contributions span from technology development, through basic neurobiologic insights from animal studies and modeling approaches, to human proof-of-principle and multicenter clinical trials. His research has been fundamental in establishing the field of therapeutic brain stimulation. His work has provided evidence for the efficacy of noninvasive brain stimulation in treating various neurologic and psychiatric conditions, including epilepsy, stroke, Parkinson disease, chronic pain, autism, and drug-resistant depression. Dr. Pascual-Leone has authored more than 600 scientific papers as well as several books, and is listed inventor in several patents. Dr. Pascual-Leone is the recipient of several international honors and awards, including the Ramón y Cajal Award in Neuroscience (Spain), the Norman Geschwind Prize in Behavioral Neurology from the American Academy of Neurology, the Friedrich Wilhelm Bessel Research Award from the Alexander von Humboldt Foundation (Germany), and the Jean-Louis Signoret Prize from the Ipsen Foundation (France). He is an elected member of the Spanish Royal Academy of Science (Farmacia).

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Grace Peng, PhDProgram Director Division of Discovery Science & Technology (DDST) National Institute of Biomedical Imaging and Bioengineering (NIBIB) National Institutes of Health (NIH)

Grace C.Y. Peng received the B.S. degree in electrical engineering from the University of Illinois at Urbana, the M.S. and Ph.D. degrees in biomedical engineering from Northwestern University. She performed postdoctoral and faculty research in the department of Neurology at the Johns Hopkins University. In 2000 she became the Clare Boothe Luce professor of biomedical engineering at the Catholic University of America. Since 2002, Dr. Peng has been a Program Director in the National Institute of Biomedical Imaging and Bioengineering (NIBIB), at the National Institutes of Health. Her program areas at the NIBIB include mathematical modeling, simulation and analysis methods, and next generation engineering systems for rehabilitation, neuroengineering, and surgical systems. In 2003, she brought together the Neuroprosthesis Group (NPG) of program officers across multiple institutes of the NIH. Also in 2003, Dr. Peng led the creation of the Interagency Modeling and Analysis Group (IMAG), which now consists of program officers from ten federal agencies of the U.S. government and Canada (www.imagwiki.org). IMAG has continuously supported funding specifically for multiscale modeling (of biological systems) since 2004. IMAG facilitates the activities of the Multiscale Modeling (MSM) Consortium of investigators (started in 2006). Dr. Peng is interested in promoting the development of intelligent tools and reusable models, and integrating these approaches in engineering systems and multiscale physiological problems.

SPEAKERSCarlos Peña, PhDDirector Division of Neurological and Physical Medicine Devices Office of Device Evaluation Center for Devices and Radiological Health Food and Drug Administration (FDA)

Carlos Peña is Division Director for the Division of Neurological and Physical Medicine Devices, in the Office of Device Evaluation, Center for Devices and Radiological Health (CDRH), at the U.S. Food and Drug Administration (FDA).

Dr. Peña is involved in all aspects of the safety and effectiveness review of neurostimulation, neurodiagnostic, neurosurgical, neurotherapeutic, and physical medicine devices. He also serves as a Principal Investigator on a FDA sponsored clinical study focused on the treatment of pediatric neurologic disorders.

Prior to joining CDRH, Dr. Peña served on detail as Assistant Director for Emerging Technologies in the Office of Science and Technology Policy (OSTP), in the Executive Office of the President of the United States. His areas of expertise included science, technology, policy, analysis, and regulatory matters related to biology, neuroscience, biotechnology, emerging technologies, agriculture, and STEM education. Before joining OSTP/FDA, Dr. Peña served at the National Institute of Neurological Disorders and Stroke, National Institutes of Health. He completed his neurosciences doctoral training at Case Western Reserve University in Cleveland, Ohio. He also attended the University of Connecticut for the Masters in Comparative Physiology, and the City College of New York, City University of New York, where he received a Bachelors specializing in Developmental Biology.

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SPEAKERSJose C. Principe, PhDDistinguished Professor of Electrical and Computer Engineering BellSouth Professor University of Florida Vice President for Technical Activities IEEE Engineering in Medicine and Biology Society

Jose C. Principe is a Distinguished Professor of Electrical and Computer Engineering at the University of Florida where he teaches advanced signal processing, machine learning and artificial neural networks (ANNs). He is BellSouth Professor and the Founder and Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL) www.cnel.ufl.edu . His primary area of research is processing of time varying signals with adaptive neural models. The CNEL Lab innovated signal and pattern recognition principles based on information theoretic criteria, as well as filtering in functional spaces. His secondary area of interest has focused in applications to computational neuroscience, Brain Machine Interfaces and brain dynamics.

Dr. Principe is a Fellow of the IEEE, AIMBE, and IAMBE. He is the past Chair of the Technical Committee on Neural Networks of the IEEE Signal Processing Society, Past-President of the International Neural Network Society (INNS), and Past-Editor in Chief of the IEEE Transactions on Biomedical Engineering. Currently he is Vice President for Technical Activities of the IEEE EMB Society and an ADCOM member of the IEEE Computational Intelligence Society (CIS). Dr. Principe received the Gabor Award, from the INNS, the Career Achievement Award from the IEEE EMBS and the Neural Network Pioneer Award, of the IEEE CIS. He has more than 700 publications and 20 patents awarded. He directed 81 PhD dissertations and 65 Master theses.

Philip A. Starr, MD, PhDProfessor of Neurological Surgery Dolores Cakebread Endowed Chair University of California, San Francisco

Philip A. Starr is currently Professor of Neurological Surgery, and holds the Dolores Cakebread endowed chair, at the University of California, San Francisco. He received his medical and doctorate degrees from Harvard Medical School, did his neurosurgery residency at Brigham and Women’s Hospital, and completed a fellowship in movement disorders surgery at Emory University. He is founder and surgical director of the largest program for deep brain stimulation in the Western USA. His NIH funded research addresses: 1) the effects of disordered basal ganglia output on cortical function in patients with movement disorders, 2) mechanisms of therapeutic deep brain stimulation, and 3) the use of totally implantable neural interfaces for long term brain recording. In addition, with UCSF colleagues Drs. Paul Larson and Alastair Martin, he has developed new surgical approaches to achieve very accurate implantation of drugs and devices at deep brain targets, using interventional MRI. Dr. Starr directs a fellowship training program in functional neurosurgery, and is past president of the American Society for Stereotactic and Functional Neurosurgery.

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SPEAKERSNitish V. Thakor, PhDProfessor of Biomedical Engineering, Electrical Engineering, Neurology Director, Neuroengineering Training Program Johns Hopkins University Editor in Chief, Medical and Biological Engineering and Computing

Nitish V. Thakor is a Professor of Biomedical Engineering at Johns Hopkins University in the USA as well as the Director of the Singapore Institute for Neurotechnology (SINAPSE) at the National University of Singapore. Dr. Thakor’s technical expertise is in the field of Neuroengineering, where he has pioneered many technologies for brain monitoring to prosthetic arms and neuroprosthesis. He is an author of more than 290 refereed journal papers, more than a dozen patents, and co-founder of 3 companies. He is currently the Editor in Chief of Medical and Biological Engineering and Computing, and was the Editor in Chief of IEEE TNSRE from 2005-2011. Dr. Thakor is a recipient of a Research Career Development Award from the National Institutes of Health and a Presidential Young Investigator Award from the National Science Foundation, and is a Fellow of the American Institute of Medical and Biological Engineering, IEEE, Founding Fellow of the Biomedical Engineering Society, and Fellow of International Federation of Medical and Biological Engineering. He is a recipient of the award of Technical Excellence in Neuroengineering from IEEE Engineering in Medicine and Biology Society, Distinguished Alumnus Award from Indian Institute of Technology, Bombay, India, and a Centennial Medal from the University of Wisconsin School of Engineering.

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SELECTED HIGHLIGHT TALKSInterrogating Neural Circuitry Underlying Neuroeconomic Decision-Making in Mouse Models of Addiction: A Functional Approach to Translation.Brian M. Sweis (1), A. David Redish (2), Mark J. Thomas (3) 1. University of Minnesota, Department of Neuroscience, Minneapolis, MN USA; 2. University of Minnesota, Graduate Programin Neuroscience, Minneapolis, MN USA; 3. University of Minnesota, School of Medicine, Minneapolis, MN, USA

Dopamine Release in the Nonhuman Primate Caudate and Putamen Depends Upon Site of Stimulation in the Subthalamic NucleusHoon-Ki Min* (1,2,3), Erika K. Ross* (1), Hang Joon Jo (1), Shinho Cho (1), Megan L. Settell (1), Ju Ho Jeong (1,4), Penelope S. Duffy (1), Su-Youne Chang (1,2), Kevin E. Bennet (1,5), Charles D. Blaha (1), and Kendall H. Lee (1,2) *1. Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA; *2. Department of Physiology and BiomedicalEngineering, Mayo Clinic, Rochester, MN, USA; *3. Department of Radiology, Mayo Clinic, Rochester, MN, USA; *4.Department of Neurosurgery, Dongguk University, Gyiongju Hospital, Gyeongbuk, Korea; *5. Division of Engineering, MayoClinic, Rochester, MN, USA. *These authors contributed equally.

Implanted Brain Computer Interface for Real-Time Cortical Control of Hand Movements in a Human with QuadriplegiaGaurav Sharma (1), Nick Annetta (1), Dave Friedenberg (1), Marcie Bockbrader (2), W. Mysiw (2), Ali Rezai (2), Chad Bouton (1,3) 1.Battelle Memorial Institute; 2.The Ohio State University, Columbus, OH; 3. Current Affiliation: Feinstein Institute for MedicalResearch, USA

Safe Direct Current Stimulation for the Treatment of Chronic Peripheral PainFei Yang (1), Yun Guan (1), Gene Fridman (2,3) 1. Anesthesiology Dept, Johns Hopkins University, Baltimore, USA; 2. Biomedical Engineering Dept, Johns Hopkins University,Baltimore, USA; 3. Otolaryngology Dept., Johns Hopkins University, Baltimore, USA

Improving Motor Recovery after Stroke by Combined rTMS and BCI TrainingNessa Johnson (1), Albert You (1), James Carey (2), Ann van de Winckel (2), Andrew Grande (3), Bin He (1,4) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Physical Therapy, University ofMinnesota, USA; 3. Department of Neurosurgery, University of Minnesota, USA; 4. Institute for Engineering in Medicine,University of Minnesota, USA

Closed-Loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms -- Is Beta Enough?Luke A. Johnson (1), Shane D. Nebeck (1), Abirami Muralidharan (1), Matthew D. Johnson (2), Kenneth B. Baker (1), Greg Molnar (1), Jerrold L. Vitek (1) 1. University of Minnesota, Department of Neurology, USA; 2. University of Minnesota, Department of Biomedical Engineering,USA

Cortical Sensing and Wearable Closed-Loop DBS in an Essential Tremor PatientJeffrey Herron (1,2), Margaret Thompson (1,2), Tim Brown (1,2), Andrew L. Ko (1,2), and Howard J. Chizeck (1,2) 1. University of Washington, Seattle, WA, USA; 2. NSF Engineering Research Center for Sensorimotor Neural Engineering(CSNE), Seattle, WA, USA

Controlling Plasticity in Sensory Cortical Regions Using Multisensory NeuromodulationCory D. Gloeckner, Jio C. Nocon, Hubert H. Lim University of Minnesota, United States, Biomedical Engineering Department

Cortical Implantation of a 16-Channel Wireless Floating Microelectrode Array (WFMA) StimulatorPhilip R. Troyk (1,2,3), David Frim (2), Ben Roitberg (2), V. Leo Towle (2), Sungjae Suh (1), Martin Bak (4), Zhe Hu (3) 1. Illinois Institute of Technology, USA; 2. University of Chicago, USA; 3. Sigenics, Inc, USA; 4. Microprobes for Life Science,USA

Investigating TMS-Evoked Cortical Responses with EEG in Chronic Stroke Whitney A. Gray, Steven L. Wolf, Michael R. Borich Department of Rehabilitation Medicine, Emory University School of Medicine, USA

MNS101

MNS111

MNS205

MNS192

MNS197

MNS124

MNS141

MNS145

MNS146

MNS160

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POSTERSInterrogating Neural Circuitry Underlying Neuroeconomic Decision-Making in Mouse Models of Addiction: A Functional Approach to Translation.Brian M. Sweis (1), A. David Redish (2), Mark J. Thomas (3)1. University of Minnesota, Department of Neuroscience, Minneapolis, MN USA; 2. University of Minnesota, Graduate Programin Neuroscience, Minneapolis, MN USA; 3. University of Minnesota, School of Medicine, Minneapolis, MN, USA.

MNS101

Micro-Coil Based Activation of CortexShelley Fried (1,2), Seung Woo Lee (2), Florian. Fallegger (3), Armin R. Völkel (3), Bernard D. F. Casse (3)1. Massachusetts General Hospital; 2. Harvard Medical School; 3.PARC, a Xerox Company, USA

Seizure Forecasting and the Preictal State in Canine EpilepsyYogatheesan Varatharajah (1), Brent M. Berry (2), Ravishankar K. Iyer (1), Gregory A. Worrell (2), Ned Patterson (3), Benjamin H. Brinkmann (2)1. University of Illinois at Urbana-Champaign, Electrical and Computer Engineering, Urbana, IL, USA; 2. Mayo Clinic, Rochester,MN, Department of Neurology & Department of Physiology & Biomedical Engineering; 3. University of Minnesota, Departmentof Veterninary Medicine, St. Paul, MN

How and Where Do Neurons Mediate Visual Perceptual Learning?: V4 and Shape Detection in Non-human PrimatesElisabeth J. Moore, Katherine Weiner, Geoffrey M. Ghose Department of Neuroscience, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN

Renal Denervation Normalizes Blood Pressure and Improves Glucose Metabolism in Obese Genetically Hypertensive Schlager Mice Ninitha Asirvatham-Jeyaraj (1), Christopher T. Banek (1), Ruijun Han (1), Maria Razzoli (1), Brandon J. Burbach (2), Alessandro Bartolomucci (1), Yoji Shimizu (2), John W. Osborn (1) 1. Department of Integrative Biology and Physiology; 2. Center for Immunology, Department of Laboratory Medicine andPathology, University of Minnesota, MN

Neuromodulatory Effects of Auditory Training on Audiovisual Speech Perception in Hearing Aid Users: A Functional Magnetic Resonance Imaging StudyLuodi Yu (1), Aparna Rao (2), Yang Zhang (2), Phillip C. Burton (1), Dania Rishiq (3), Harvey Abrams (4) 1. University of Minnesota, Twin-Cities, MN, USA; 2. Arizona State University, AZ, USA; 3. Mayo Clinic, FL, USA; 4. StarkeyHearing Technologies, MN, USA.

Source Imaging of Brain Activation by Low-intensity Transcranial Focused UltrasoundKai Yu (1), Abbas Sohrabpour (1), and Bin He (1,2)1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Institute for Engineering in Medicine, University ofMinnesota, USA

Dopamine Release in the Nonhuman Primate Caudate and Putamen Depends Upon Site of Stimulation in the Subthalamic Nucleus Hoon-Ki Min* (1,2,3), Erika K. Ross* (1), Hang Joon Jo (1), Shinho Cho (1), Megan L. Settell (1), Ju Ho Jeong (1,4), Penelope S. Duffy (1), Su-Youne Chang (1,2), Kevin E. Bennet (1,5), Charles D. Blaha (1), and Kendall H. Lee (1,2) *1. Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA; *2. Department of Physiology and BiomedicalEngineering, Mayo Clinic, Rochester, MN, USA; *3. Department of Radiology, Mayo Clinic, Rochester, MN, USA; *4.Department of Neurosurgery, Dongguk University, Gyiongju Hospital, Gyeongbuk, Korea; *5. Division of Engineering, MayoClinic, Rochester, MN, USA. *These authors contributed equally.

Decoding Natural Motor Imagination Tasks Through Cortical Currents for Intuitive Brain-Computer Interface Use Bradley J. Edelman (1), Bryan B. Baxter (1), Bin He (1,2) 1. Department of Biomedical Engineering, University of Minnesota, MN, USA; 2. Institute for Engineering in Medicine,University of Minnesota, MN, USA

MNS106

MNS112

MNS111

MNS109

MNS108

MNS104

MNS103

MNS110

The Learning Effect With Respect to Channel Configuration for Online Brain-Computer InterfaceJianjun Meng (1), Jaron Olsoe (1), Gabriel Jacobs(1), Shuying Zhang (1), Angeliki Beyko (2) and Bin He (1,2) 1. Department of Biomedical Engineering; 2. Institute for Engineering in Medicine, University of Minnesota

MNS115

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POSTERSTowards a Closed-Loop Deep Brain Stimulation Treatment for Essential TremorEnrico Opri (1), Jonathan Shute (1), Rene Molina (2), Kelly Foote (3), Michael Okun (3), Aysegul Gunduz (1,2,3) 1.J. Crayton Pruitt Department of Biomedical Engineering; 2. Department of Electrical Engineering; 3. Center for MovementDisorders and Neurorestoration, University of Florida, Gainesville, FL

Brain-Context Interactions in Tic Suppression: Description of a New Methodology Integrating rTMS and a Behavioral Experimental ParadigmChristine Conelea (1,2), Brianna Wellen (2), Benjamin Greenberg (1,3) 1. Alpert Medical School of Brown University; 2. Bradley Hospital; 3. Butler Hospital

3D Bioprinting Conductive Nano Scaffold With Multi-Walled Carbon Nanotubes for Improved Nerve GenerationSe-Jun Lee (1), Lijie Grace Zhang (1,2) 1. Department of Mechanical and Aerospace Engineering, The George Washington University; 2. Department of Medicine, TheGeorge Washington University

The Inhibition Function of Responsive Stimulation on Penicillin Induced Absence Epilepsy in RatsYechao Han (1,2), Kedi Xu (1,2), Xiaoxiang Zheng (1,2) 1. Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; 2. Department of BiomedicalEngineering, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University

Integration of Transcranial Direct Current Stimulation and Electroencephalography for the Study of Binocular RivalryAbhrajeet Roy (1), Bradley Edelman (1), Angeliki Beyko (1), Sheng He (2), Steve Engel (2), Bin He (1,3) 1. Department of Biomedical Engineering, University of Minnesota; 2. Department of Psychology, University of Minnesota; 3.Institute for Engineering in Medicine, University of Minnesota

Soft Drink Effects on Sensorimotor Rhythm Brain Computer Interface Performance and Resting-State Spectral PowerJohn Mundahl (1), Jianjun Meng (1), Jeffrey He (2), Bin He (1,3) 1. Dept. of Biomedical Engineering, University of Minnesota, USA; 2. Mounds View High School, USA; 3. Institute forEngineering in Medicine, University of Minnesota, USA

Implanted Brain Computer Interface for Real-Time Cortical Control of Hand Movements in a Human with QuadriplegiaGaurav Sharma (1), Nick Annetta (1), Dave Friedenberg (1), Marcie Bockbrader (2), W. Mysiw (2), Ali Rezai (2), Chad Bouton (1,3) 1.Battelle Memorial Institute; 2.The Ohio State University, Columbus, OH; 3. Current Affiliation: Feinstein Institute for MedicalResearch, USA

Renal Nerves, Renal Inflammation and Hypertension in Deoxycorticosterone Acetate (DOCA)-Salt Hypertension: Who is in the Driver’s Seat?Christopher T. Banek, Jason D. Foss, Dusty A. Van Helden, Ninitha Asirvatham-Jeyaraj, and John W. Osborn University of Minnesota Medical School, USA

Stimulation Amplitude-Dependent Changes in Neuronal Activity Around a Chronically Implanted Thalamic Deep Brain Stimulation ArrayYiZi Xiao (1), Matthew D. Johnson (1,2) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Institute for Translational Neuroscience, University of Minnesota, USA

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Neuronix Enables Continuous, Simultaneous Neural Recording and Electrical MicrostimulationAnh T. Nguyen, Tong Wu, Jian Xu, and Zhi Yang Biomedical Engineering, University of Minnesota Twin Cities

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A Case Report of Visual and Motor Recovery After Cognitive Sensorimotor Rehabilitation in a Patient with Cortical BlindnessDaniele De Patre (1), Franca Panté (1), Carla Rizzello (1), Marina Zernitz (1), Mariam Mansour (2), Lara Zordan (3), Thomas Zeffiro (4), Erin O. Connor (5), Teresa Bisson (6), Andrea Lupi (7), Carlo Perfetti (1), Ann Van de Winckel (6) 1. Centro Studi di Riabilitazione Neurocognitiva Villa Miari, Italy; 2. Unità Operativa di Neuroradiologia di Vicenza, Italy; 3. UnitàOperativa Complessa di Neurochirurgia di Vicenza, Italy; 4. Neurometrika, USA; 5. Temple University School of Medicine, USA;6. University of Minnesota, USA; 7. Unità Operativa Complessa di Medicina Nucleare di Vicenza, Italy

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POSTERSSpatial Distributions of Subthalamic Oscillations in Parkinson’s Disease During Resting and MovementXinyi Geng (1), Xin Xu (2), Yongzhi Huang (1), Zhipei Ling (2), Shouyan Wang (1) 1. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, China; 2. General Hospital ofPLA, China

Fast Mapping of Brain Electrical Properties Using MRI – A Simulation StudyYicun Wang (1), Pierre-Francois Van de Moortele (2), Bin He (1,3) 1. Department of Biomedical Engineering, University of Minnesota; 2. Center for Magnetic Resonance Research, University ofMinnesota; 3. Institute for Engineering in Medicine, University of Minnesota

Effect of Renal Denervation and Celiac Ganglionectomy on Mean Arterial Pressure in the Hypertensive Schlager (BPH/2J) MouseMadeline M. Gauthier, Claire Breitenstein, Ninitha Asirvatham-Jeyaraj, and John W. Osborn Department of Integrative Biology and Physiology, University of Minnesota-Twin Cities, USA

Identifying Optimal Electromyography Responses in Infants with Perinatal Stroke: The Foundation for a Novel Transcranial Magnetic Stimulation ProtocolChao-Ying Chen (1), Mo Chen (2), Bernadette Gillick (1,3) 1. Department of Physical Medicine and Rehabilitation, Medical School, University of Minnesota; 2. University of Minnesota,Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab; 3. Program of Physical Therapy, RehabilitationScience Program, Department of PM&R, Medical School, University of Minnesota

A Comparison of Paretic and Non-Paretic Hand Electromyographic Responses with Single-Pulse Transcranial Magnetic Stimulation Testing in Children with Congenital HemiparesisTonya L. Rich (1), Chao-Ying Chen (1), Maíra C. Lixandrão (1,2) Bernadette T. Gillick (1) 1. University of Minnesota, Program in Rehabilitation Science, USA; 2. Federal University of Sao Carlos, Department ofPhysical Therapy, Brazil

Transcranial Focused Ultrasound for Primary Motor Cortex Stimulation in HumansLeo Ai, Jerel K. Mueller, Priya Bansal, Wynn Legon University of Minnesota, USA, Department of Physical Medicine and Rehabilitation

rTMS and Finger Tracking Training in a Single Subject with Chronic Brainstem StrokeKate Frost (1), Thomas Broback (2), Nicole Carlson (2), Caitlin Daggett (2), Megan Dalbec (2), James R. Carey (1,2) 1. Program in Rehabilitation Science, University of Minnesota, Minneapolis, MN; 2. Department of Physical Therapy, Universityof Minnesota, Minneapolis, MN

The Effects of Anodal tDCS Over the Supplementary Motor Area on Gait Initiation in People with Parkinson’s Disease with Freezing of GaitSommer L. Amundsen Huffmaster (1,2), Chiahao Lu (1,2), Paul J. Tuite (2), Colum D. MacKinnon (1,2) 1. Movement Disorders Lab, University of Minnesota; 2. Department of Neurology, University of Minnesota.

Astrocytes Stimulation of Magneto-electric Nanoparticles outside Brain Blood BarrierKun Yue, and Alice C. Parker Ming Hsieh Department of Electrical Engineering, University of Southern California, USA

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Reducing Impulsivity and Risk-Taking Behavior Using Transcranial Direct Current StimulationCasey S. Gilmore (1,2), Molly R. Carson (1,2), Carolyn L. Gentz (1,2), Patricia J. Dickmann (2,3), Greg J. Lamberty (2,3), Michael T. Armstrong (2), Kelvin O. Lim (1,2,3) 1.Defense and Veterans Brain Injury Center, Minneapolis, MN; 2. Minneapolis VA Health Care System, Minneapolis, MN;3. Dept. of Psychiatry, University of Minnesota, Minneapolis, MN

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Inter-Individual Differences in the Induced Electric Field from Transcranial Magnetic StimulationE. G. Lee (1), R. L. Hadimani (2,1), D. C. Jiles (1) 1. Dept. of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA; 2. Dept. of Mechanical and NuclearEngineering, Virginia Commonwealth University, Richmond, Virginia, USA

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POSTERSSafe Direct Current Stimulation for the Treatment of Chronic Peripheral PainFei Yang (1), Yun Guan (1), Gene Fridman (2,3) 1. Anesthesiology Dept, Johns Hopkins University, Baltimore, USA; 2. Biomedical Engineering Dept, Johns Hopkins University,Baltimore, USA; 3. Otolaryngology Dept., Johns Hopkins University, Baltimore, USA

Developing a Microfluidic Device for Safe DC StimulationAnnie Mao (1), Patrick Ou (1), Kevin King (1,2), Gene Fridman (1) 1. Johns Hopkins University, USA; 2. University of Pittsburgh, USA

Bilateral Cortical Silent Period Evoked By Transcranial Magnetic Stimulation in a Child with Perinatal Stroke: Understanding Cortical Inhibitory CircuitsMaíra C. Lixandrão (1,2) ; Tonya Rich (2); Chao-Ying Chen (2); Bernadette Gillick (2) 1. Federal University of Sao Carlos, Brazil; 2. University of Minnesota, United States

The Influence of Corticospinal Tract Activation on Cortical Connectivity Evaluation: A TMS-EEG Study Nessa Johnson (1), Sara Petrichella (1,2), Bin He (1,3) *1. Department of Biomedical Engineering, University of Minnesota, USA; *2. Department of Computer Science and ComputerEngineering, University Campus Bio-Medico, Italy; *3. Institute for Engineering in Medicine, University of Minnesota, USA;*These authors contributed equally.

Improving Motor Recovery after Stroke by Combined rTMS and BCI TrainingNessa Johnson (1), Albert You (1), James Carey (2), Ann van de Winckel (2), Andrew Grande (3), Bin He (1,4) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Physical Therapy, University ofMinnesota, USA; 3. Department of Neurosurgery, University of Minnesota, USA; 4. Institute for Engineering in Medicine,University of Minnesota, USA

Closed-Loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms -- Is Beta Enough?Luke A. Johnson (1), Shane D. Nebeck (1), Abirami Muralidharan (1), Matthew D. Johnson (2), Kenneth B. Baker (1), Greg Molnar (1), Jerrold L. Vitek (1) 1. University of Minnesota, Department of Neurology, USA; 2. University of Minnesota, Department of Biomedical Engineering,USA

Phase-Amplitude Coupling in the STN and its Change Following Therapeutic STN DBS in the MPTP Monkey Model of Parkinson’s DiseaseJing Wang (1), Shane Nebeck (1), Luke A. Johnson (1), Jianyu Zhang (1), Matthew D. Johnson (2), Kenneth B. Baker (1), Jerrold L. Vitek (1) 1. Department of Neurology, University of Minnesota, USA; 2. Department of Biomedical Engineering, University of Minnesota,USA

Effects of Short-Term Mind-Body Awareness Training on Sensorimotor Rhythm based Brain-Computer InterfaceJames R. Stieger (1), Christopher C. Cline (1), Andy Huynh (1), Angeliki Beyko (1), Stephen A. Engel (2), Bin He (1,3) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Psychology, University of Minnesota,USA; 3. Institute for Engineering in Medicine, University of Minnesota, USA

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Sensitivity Analysis of Transcranial Magnetic Stimulation: A Computational Modeling StudyChristopher C. Cline (1), Nessa N. Johnson (1), Bin He (1,2) 1. Department of Biomedical Engineering, University of Minnesota; 2. Institute for Engineering in Medicine, University ofMinnesota

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Sensorimotor Rhythm BCI with Simultaneous High Definition-Transcranial Direct Current Stimulation Alters Task PerformanceBryan S. Baxter (1), Bradley Edelman (1), Nicholas Nesbitt (1), Bin He (1,2) 1. Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA; 2. Institute for Engineering inMedicine, University of Minnesota, Minneapolis, MN, USA

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An Externalised Mobile System for Closed-Loop Deep Brain Stimulation Research in PatientsYunpeng Zhang (1), Liang Li (1), Alek Pogosyan (2), Peter Brown (2), Shouyan Wang (1) 1. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China; 2. MedicalResearch Council Brain Network Dynamics Unit at University of Oxford, Oxford, UK

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POSTERSImmunohistochemical Evaluation of Deep Brain Stimulation Induced Neural ActivationBenjamin A. Teplitzky (1), Matthew D. Johnson (1,2) 1. Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN; 2. Institute for TranslationalNeuroscience, University of Minnesota, Minneapolis, MN

Python-based Open-Source Stereotactic Neurosurgical Planning Software PackageDiana Johnson (1), Simeng Zhang (1), Matthew D. Johnson (1,2) 1. Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA; 2. Institute for Translational Neuroscience,University of Minnesota, Minneapolis, Minnesota, USA

Particle Swarm Optimization for Programming DBS ArraysSimeng Zhang, Edgar Peña, YiZi Xiao, Steve Deyo, Matthew D. Johnson Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA

Seizure Resulting from Deep Transcranial Magnetic Stimulation in an Adolescent with Depression: a Case ReportKathryn R. Cullen (1), Suzanne Jasberg (1), Bonnie Klimes-Dougan (2), Paul Croarkin (3), Kelvin O. Lim (1), Brent Nelson (1) 1.University of Minnesota, Department of Psychiatry, USA; 2. University of Minnesota, Department of Psychology, USA; 3. Mayo Clinic

Cortical Sensing and Wearable Closed-Loop DBS in an Essential Tremor Patient Jeffrey Herron (1,2), Margaret Thompson, (1,2) Tim Brown (1,2), Andrew L. Ko (1,2), and Howard J. Chizeck (1,2) 1. University of Washington, Seattle, WA; 2. NSF Engineering Research Center for Sensorimotor Neural Engineering CSNE,Seattle, WA

An Unsupervised Algorithm for Neural Spike Sorting Inspired by Superparamagnetic ClusteringBrendan Hasz (1) and A. David Redish (2) 1. Graduate Program in Neuroscience, University of Minnesota Twin Cities; 2. Department of Neuroscience, University ofMinnesota Twin Cities

Predictive and Feedback Motor Signals in the Output of Cerebellar Purkinje CellsMartha L. Streng (1), Laurentiu S. Popa (2), Timothy J. Ebner (1,2) 1. Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN; USA. 2. Department of Neuroscience,University of Minnesota, Minneapolis, MN, USA

Optimizing Cerebellar Transcranial Direct Current Stimulation for Lower Limb Visuomotor LearningAnirban Dutta (1), Águida Foerster (1), Michael A. Nitsche (1,2) 1. Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund, Germany; 2. Department ofNeurology, University Medical Hospital Bergmannsheil, Germany

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MNS166 Resting State Source Imaging Analysis of Sickle Cell Disease Patients using EEGSina Shirinpour (1), Michelle Case (1), Yvonne Datta (1), Stephen Nelson (2), Kalpna Gupta (1), Bin He (1) 1. University of Minnesota, USA; 2. Children’s Hospitals and Clinics of Minnesota, USA

EEG-fNIRS Based Assessment of Neurovascular Coupling During Anodal Transcranial Direct Current Stimulation - Parameter Estimation with an Autoregressive Model in StrokeAnirban Dutta (1), Mitsuhiro Hayashibe (3), David Guiraud (3), Michael A. Nitsche (1,2) 1. Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund, Germany; 2. Department ofNeurology, University Medical Hospital Bergmannsheil, Germany; 3. INRIA and Université de Montpellier, Montpellier, France

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Classification of Tonic Pain and Rest Conditions using EEG dataVishal Vijayakumar, Michelle Case, Clara Huishi Zhang, Bin He University of Minnesota, USA

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Can Short-Interval Intracortical Inhibition be Modulated by Low Frequency Repetitive Transcranial Magnetic StimulationMo Chen (1), Teresa J. Kimberley (2) 1. University of Minnesota, Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab;2. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy andRehabilitation Science

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Laryngeal Motor Cortex Excitability Assessment Using Transcranial Magnetic StimulationMo Chen (1), Rebekah L. Schmidt (2), Cecilia N Prudente (2), George Goding (3), Teresa J. Kimberley (2) 1. University of Minnesota, Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab;2. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy andRehabilitation Science; 3. University of Minnesota, Department of Otolaryngology-Head and Neck Surgery

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POSTERS

Reinforcement Learning for Phasic Disruption of Pathological Oscillations in a Model of Parkinson’s DiseaseLogan L Grado (1), Matthew D Johnson (1,2), Theoden I Netoff (1) 1. Graduate Program in Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA; 2. Institute forTranslational Neuroscience, University of Minnesota, Minneapolis, Minnesota, USA

Multivariate Pattern Analysis of fMRI Data Reveals the Discrete Neural Signature of Target-Specific Deep Brain Stimulation.Shinho Cho (1), Paola Testini (1), Megan Settell (1), Hang Joon Jo (1), Paul Min (1,2), Kendall H. Lee (1,2) 1. Department of Neurologic Surgery; 2. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN

16-Channel Automatic Multiple Electrode Tester (MET16) for Implanted Cortical MicroelectrodesPhilip Troyk (1,2) Zhe Hu (2), Glenn DeMichele (2)1. Department of Biomedical Engineering, Illinois Institute of Technology, Chicago IL; 2. Sigenics Inc., Chicago IL;

Vagus Nerve Stimulation Combined with Rehabilitation for the Upper Extremity After StrokeCecilia N. Prudente (1), Teresa Bisson (1), Danielle Kline (1), Kate Frost (1), Stephen J. Haines (2), David Pierce (3), Navzer Engineer (3), Teresa J. Kimberley (1) 1. Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy and Rehabilitation Science, University ofMinnesota; 2. Department of Neurosurgery, University of Minnesota; 3. Microtransponder, Inc.

On-Chip Data Compression for Large-Scale Neural RecordingTong Wu, Wing-kin Tam, and Zhi Yang Biomedical Engineering, University of Minnesota Twin Cities, MN, USA

Tactile Sensor Development for Upper Limb ProsthesesKory Jenkins, Rusen Yang University of Minnesota, USA

Designing a Multi-Electrode Array Compatible with Ultrahigh Field MRICorey Cruttenden (1), Hannes Wiesner (2), Xiao-Hong Zhu (2), Wei Chen (2), Rajesh Rajamani (1) 1. Department of Mechanical Engineering; 2. Center for Magnetic Resonance Research, University of Minnesota, Minneapolis,MN, USA

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Effect of Parkinsonism and Deep Brain Stimulation on Phase-Amplitude Correlations in Macaque Globus Pallidus and Motor Cortex David Escobar (1), Luke Johnson (1), Shane Neback (1), Matthew Johnson (2), Kenneth Baker (1), Gregory F. Molnar (1), Jerrold L. Vitek (1) 1. University of Minnesota, Department of Neurology; 2. University of Minnesota, Department of Biomedical Engineering

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A Transient Model for Neuronal OscillationsCarlos Loza, Jose Principe Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA

MEG Source Imaging of Epileptic ActivityShuai Ye (1), Abbas Sohrabpour (1), Wenbo Zhang (2), Bin He (1,3) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Minnesota Epilepsy Group, USA; 3. Institute forEngineering in Medicine, University of Minnesota, USA

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Intercostal Cryoanalgesia in the Ovine ModelAdam W. Cates (1), Laurie A. Yunker (1), Daniel Lafontaine (1), Christina Gross (2), Lynette Phillips (2), Bob Trusty (1), Tamer Ibrahim (1), Steven F. Bolling (3) 1. AtriCure, Inc., Minnetonka, MN; 2. American Preclinical Services, Minneapolis, MN; 3. University of Michigan, Ann Arbor, MI.

Safe Direct Current Stimulation Increases the Dynamic Range of Head Velocities Encoded by the Vestibular ProsthesisYu (Erin) Zheng, Dilawer Singh, Gene Y. Fridman Johns Hopkins University, Department of Otolaryngology Head and Neck Surgery, Department of Biomedical Engineering

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POSTERSDevelopment of Deep Brain TMS Coil: Triple Halo CoilPriyam Rastogi (1), Ravi Hadimani (2,1), David Jiles (1) 1. Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, USA; 2. Department of Mechanicaland Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, USA.

Suppressing Seizures Using Linear Quadratic Gaussian ControlVivek Nagaraj (1), Andrew Lamperski (3), Theoden I Netoff (1,2) 1. Graduate Program in Neuroscience; 2. Department of Biomedical Engineering; 3. Department of Electrical and ComputerEngineering; University of Minnesota Twin-Cities, USA

Accelerating Patient Access to Neuromodulation Therapies: A Practical Tool to Demonstrate Neural Tissue SafetyGregory F. Molnar (1,2), Dawn Bardot (1), Kyle J. Myers (3), Bill Murray (1), Randall Schiestl (4), MDIC Computer Modeling & Simulation Project Team (1) 1. Medical Device Innovation Consortium (MDIC), USA; 2. Department of Neurology, University of Minnesota School ofMedicine, USA; 3. Office of Science & Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food andDrug Administration, USA; 4. Boston Scientific Corporation, USA.

Sparse Electromagnetic Source Imaging: A Periscope to Guide Neuromodulation TherapiesAbbas Sohrabpour (1), Yunfeng Lu (1,2), Gregory Worell (3), Bin He (1.4) 1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Medtronic, USA; 3. Neurology Department, MayoClinic, USA; 4. Institute for Engineering in Medicine, University of Minnesota, USA

Temporal Discretization Errors Produce Minimal Effects on Vestibular Prosthesis PerformancePeter J. Boutros (1,2), Nic Valentin (2), Dale Roberts (2), Kristin N. Hageman (1), Chenkai Dai (2), Charles C. Della Santina (1,2) 1. Johns Hopkins University, Department of Biomedical Engineering, USA; 2. Johns Hopkins University, Department ofOtolaryngology – Head & Neck Surgery, USA

Characterization of Cortical SMA-M1 Neurophysiological Activity in the MPTP Nonhuman Primate Model of Parkinson’s Disease During a Goal Directed Reach TaskBrett A. Campbell (1), Claudia M. Hendrix (1), Zachary Weinstock (2), Yasaman Adibi (1), Kenneth Baker (1), Jerrold Vitek (1) 1. University of Minnesota, Department of Neurology, Center for Neuromodulation Research, USA; 2. University of MinnesotaCollege of Biological Sciences, USA

Deciphering Generalized Epileptic Networks with Multimodal NeuroimagingZhiyi Sha (1), Clara H. Zhang (2), Abbas Sohrabpour (2), Thomas Henry (1), Bin He (2,3) 1. Department of Neurology, University of Minnesota, USA; 2. Department of Biomedical Engineering, University of Minnesota,USA; 3. Institute for Engineering in Medicine, University of Minnesota, USA

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Design of a Vestibular Prosthesis for Sensation of Gravitoinertial AccelerationKristin N. Hageman (1), Margaret R. Chow (1), Peter J. Boutros (1), Dale Roberts (2), Angela Tooker (2), Kye Lee (3), Sarah Felix (3), Satinderpall S. Pannu (3), Charles C. Della Santina (1,2)1. Departments of Biomedical Engineering; 2. Otolaryngology - Head & Neck Surgery, Johns Hopkins School of Medicine,Baltimore, MD; 3. Lawrence Livermore National Laboratory, Livermore, CA

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Optogenetic Self-Stimulation of the Infralimbic-Accumbens Pathway: Opposing Effects of Abstinence from Repeated Cocaine and Cocaine Re-exposureA. Asp, E. B. Larson, M. Esguerra, M. C. Hearing, K. A. Silvis, C. Zhang, M. J. ThomasNeuroscience, Univ. of Minnesota, Minneapolis, MN

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Controlling Plasticity in Sensory Cortical Regions Using Multisensory NeuromodulationCory D. Gloeckner, Jio C. Nocon, Hubert H. Lim University of Minnesota, United States, Biomedical Engineering Department

180-Day, In Vivo Study of Electrodeposited PtIr Electrodes for NeuromodulationArtin Petrossians (1), John J. Whalen III (1,2), James D. Weiland (1,2)1. Department of Ophthalmology, University of Southern California, Los Angeles, CA, USA; 2. USC Institute for BiomedicalTherapeutics, University of Southern California. Los Angeles, CA, USA

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POSTERSDeep Brain Stimulation Using Rotating and Spatially Selective E-fieldsLauri J. Lehto (1), Lynn Utecht (1), Matthew Johnson (2), Olli Grohn (3), and Shalom Michaeli (1) 1. CMRR, University of Minnesota, USA; 2. Department of Biomedical Engineering, University of Minnesota, USA; 3. Universityof Eastern Finland, Finland

Low frequency Desynchronization in the Supplementary Motor Area (SMA) of Healthy and Parkinsonian Nonhuman Primates (NHPs).Yasaman Adibi, Claudia Hendrix, Brett Campbell, Kenneth Baker, Jerrold L. Vitek University of Minnesota, Department of Neurology, Center for Neuromodulation Research

Cortical Implantation of a 16-Channel Wireless Floating Microelectrode Array (WFMA) StimulatorPhilip R. Troyk (1,2,3), David Frim (2), Ben Roitberg (2), V. Leo Towle (2), Sungjae Suh (1), Martin Bak (4), Zhe Hu (3) 1. Illinois Institute of Technology, USA; 2. University of Chicago, USA; 3. Sigenics, Inc, USA; 4. Microprobes for Life Science,USA

Phasic Burst Stimulation: A Novel Approach for Optimizing Closed-Loop Deep Brain StimulationAbbey Holt, Max Shinn, Theoden Netoff University of Minnesota

Cerebellar tDCS Interferes with Cortical Excitability During a Motor Training TaskRebekah Summers (1), Mo Chen (2), Cecilia N. Prudente (1), Teresa J. Kimberley (1) 1. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy andRehabilitation Science; 2. University of Minnesota, Institute for Engineering in Medicine

A Miniaturized Brain-Machine-Spinal Cord Interface (BMSI) for Closed-Loop Intraspinal MicrostimulationShahab Shahdoost (1), Shawn Frost (2), David Guggenmos (2), Caleb Dunham (2), Jordan Borrell (2), Scott Barbay (2), Vanessa Tolosa (3), Randolph Nudo (2), Pedram Mohseni (1) 1. Case Western Reserve University, USA; 2. University of Kansas Medical Center, USA; 3. Lawrence Livermore NationalLaboratory, USA

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In-vitro Examination of Epileptic Seizure Suppression Mechanism by Electrical StimulationSora Ahn, Sumin Jo, Hyang Woon Lee, Sang Beom Jun and Seungjun Lee Ewha Womans University

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Patient-Specific Models of Local Field Potentials Recorded from Deep Brain Stimulation ElectrodesNicholas Maling (1), Scott Lempka (2,3), Cameron McIntyre (1,3) 1. Case Western Reserve University, Dept. of Biomedical Engineering, Cleveland, OH; 2. Cleveland Clinic Center forNeurological Restoration, Cleveland OH; 3. Cleveland VA Medical Center, Cleveland OH

Investigating TMS-Evoked Cortical Responses with EEG in Chronic StrokeWhitney A. Gray, Steven L. Wolf, Michael R. Borich Department of Rehabilitation Medicine, Emory University School of Medicine, USA

Investigation of an Optogenetics-Based Multi-Site Motor Cortical Neuromodulation Method for the Treatment of Parkinson’s DiseaseZeyang Yu (1), Janos Perge (1), Wael Asaad (1,2), Arto Nurmikko (1), Ilker Ozden (1) 1. Brown University, USA; 2. Rhode Island Hospital, USA

Differential Effects of Noisy and Sinusoidal Galvanic Vestibular Stimulation on Resting-State Functional ConnectivitySoojin Lee (1,4), Jiayue Cai (2), Diana J. Kim (3), Z. Jane Wang (2), Martin J. McKeown (3,4) 1. Department of Biomedical Engineering, University of British Columbia, Canada; 2. Department of Electrical and ComputerEngineering, University of British Columbia, Canada; 3. Department of Medicine, University of British Columbia, Canada; 4.Pacific Parkinson’s Research Centre, University of British Columbia, Canada

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Title: Interrogating neural circuitry underlying neuroeconomic decision-making in mouse models of addiction: Afunctional approach to translation.

Authors: Brian M. Sweis2,3, A. David Redish1, Mark J. Thomas1

Affiliations:1. University of Minnesota, Department of Neuroscience, Minneapolis, MN USA 55455.2. University of Minnesota, Graduate Program in Neuroscience, Minneapolis, MN USA 55455.3. University of Minnesota, School of Medicine, Minneapolis, MN, USA 55455.

Background:Deliberative decision-making comprises numerous capabilities: integrating sensory inputs, assessing motivation, evaluating consequences, and executing coordinated actions. New theories see neuropsychiatric disorders like addiction resulting from failure modes in such decision-making processes.1 Traditional translational paradigms are based on creating models of disease in animals that measure, for example, the effects of cocaine in self-administering rodents. Such approaches ask how drugs affect animal behavior and look for mechanistic explanations, which are then looked for in humans. Our work instead poses a functional approach to translation where we ask what the neural mechanisms are in addicted humans and whether modulating the functionality of those circuits in animals will produce the same aberrant behavioral effects. A human addict might be less willing to wait for a reward than a non-addicted individual. Instead of asking whether addicted rodents are also less willing to wait for a reward, we ask what are the neurophysiological changes that underlie that impulsivity in human drug-dependent users, and how can we impose those neurophysiological changes in rodents. If that drives impulsivity in rodents, then we can ask how to treat those neurophysiological changes (to return rodent impulsivity back to normal). These treatments are more likely to translate back to humans.

MethodsWe developed a novel task based on human neuroeconomic approaches to study decision-making in mice.2 This is part of a larger collaboration translating the very same task into healthy humans and neuropsychiatric patients coupled with neuroimaging approaches.3 The first experiment examined the effects of cocaine on decision-making in mice (traditional paradigm). The second two experiments used optogenetic interventions in drug naïve mice to modulate corticostriatal circuits in two ways: (1) induction of plasticity and (2) transient modulation of on-going behavior (functional approachesto translation paradigms).

ResultsCocaine seemed to alter willingness to wait for rewards, or impulsivity, seen at a time point during cocaine withdrawal known to alter synaptic strength of corticostriatal circuits. Optogenetic induction of this neurophysiological change in drug naïve mice seemed to mimic this effect, which also seemed to be reversed by inducing opposing neurophysiological changes.

ConclusionsOur work explores how neuroplasticity in specific circuits in the brain alters neuroeconomic decision-making and howthese vulnerabilities may underlie maladaptive goal-oriented behavior. Preliminary findings suggest how we might restore normal decision-making function using precise neuromodulation techniques. This creates new opportunities for addiction treatment and may shed light on reward circuit dysfunction in other neuropsychiatric disorders such as anxiety, schizophrenia, and depression.

References1. Redish, AD. "Addiction as a symptom of failure modes in the machineries of decision-making." Chapter 7 inHandbook on the Cognitive Neuroscience of Addiction (ed., Wilson, S. J.) 151–172, (2015).2. Steiner, AP & Redish, AD. Behavioral and neurophysiological correlates of regret in rat decision-making on aneuroeconomic task. Nature Neuroscience. 17, 995–1002, (2014).3. Abram, SV, Brenton, Y, Schmidt, B, Redish, AD, MacDonald, AW 3rd. The Web-Surf Task: A translational model ofhuman decision-making. CABN. (2015).

FundingUniversity of Minnesota MSTP training grant NIGMS 5T32GM008244-25, Neuroscience training grant NIGMS grant 5T32GM008471-22, and the MnDRIVE Neuromodulation Pre-Doctoral Fellowship.

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Title: Micro-coil based activation of cortex

Authors: Shelley Fried1,2, Seung Woo Lee2, Florian. Fallegger3, Armin R. Völkel3, Bernard D. F. Casse3

Affiliations:1. Massachusetts General Hospital, USA; 2. Harvard Medical School, USA; 3. PARC, a Xerox Company,USA

Background: Intra-cortical micro-stimulation (ICMS) has the potential to treat a wide range of neurological and psychological diseases. Unfortunately, the long-term effectiveness of the implants that can deliver such stimulation has been limited, in part due to the complex biological and chemical reactions that diminish the effectiveness of individual electrodes over time. Magnetic stimulation could theoretically overcomethis limitation, e.g. unlike electric fields, magnetic fields are not impeded by the encapsulating glial scarring that envelops electrodes over time. However, it is not clear whether coils that are small enough to be implanted into cortex could effectively modulate neural activity. If effective, the spatially asymmetric nature of the fields arising from coils might facilitate selective targeting of specific cell types within the highly-structured cortical architecture, thereby providing a second important advantage over conventional electrodes.

MethodsA computational model was developed to compare the fields induced by different coil designs and the most promising designs were fabricated for use in electrophysiological experiments. Coronal slices from the mouse brain allowed the sensitivity of individual Layer 5 pyramidal neurons (L5PNs) to be systematically tested. Coils were also implanted into the whisker (motor) portion of mouse cortex in vivoto explore whether behavioral responses could be induced.

ResultsIn vitro testing revealed that L5PNs from motor, pre-frontal and visual cortices could all be activated by magnetic stimulation from the micro-coil (50x200 µm profile). Mapping responses in individual L5PNs revealed that the region around the proximal axon had the highest sensitivity to individual pulses but that portions of the apical dendrite were more sensitive to repetitive stimulation. Only those coil orientations that induced a strong electric field along the length of the pyramidal neuron were effective; L5PNs were not activated by other orientations of the coil. Insertion of the coils into whisker cortex in vivo led to activation of single whiskers, or multiple whiskers, depending on the depth of penetration.

Conclusions In vivo stimulation with micro-coils matched many of the physiological responses obtained in earlier studies with ICMS (electric stimulation). In addition, the coil orientation experiments suggest that the region of activation is confined to a focal region around the coil. This will be essential for applications such as a visual prosthetic as it will improve the spatial resolution that can be obtained by the device. These features, along with the reduced susceptibility to encapsulation suggest that a coil-based implantcould supplant conventional electrode-based devices.

FundingRappaport Foundation, NIH R01 EY023651 and VA RR&D 1I01RX001663.

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Minnesota Neuromodulation Symposium, April 2016 MNS 103

Yogatheesan Varatharajah1, Brent M. Berry2 Ravishankar K. Iyer1, Gregory A. Worrell2, Ned Patterson3 Benjamin H.Brinkmann2

Affiliations:1. University of Illinois at Urbana-Champaign, Electrical and Computer Engineering Urbana, IL 61801, USA. 2. MayoClinic Rochester MN, Department of Neurology & Department of Physiology & Biomedical Engineering 3. Universityof Minnesota Department of Veterinary Medicine, St. Paul MN

Background:

The ability to predict seizures could enable patients with epilepsy to better manage their medications and activities,potentially reducing medication side effects and improving quality of life. Forecasting epileptic seizures remains achallenging problem, but machine learning methods with intracranial electroencephalographic (iEEG)measures have shown promise. This is a necessary step in the creation of a closed-loop device which can inform stimulation of epileptogenic tissue at some time period before a seizure might occur.

Methods:

The NeuroVista Seizure Advisory System was implanted in eight canine subjects with naturally occurring epilepsy andspontaneous seizures. The dogs were housed in the University of Minnesota and University of Pennsylvania veterinaryclinics. The subjects were continuously monitored with video and iEEG. Antiepileptic medications were provided asneeded to the dogs during this study. Five dogs had an adequate number of seizures and prolonged interictal recordingssuitable for analysis.

A machine learning based pipeline was developed to process iEEG recordings and generate seizure warnings. In chronicambulatory iEEG recordings from canines with naturally occurring epilepsy the relative effectiveness of different derivedfeatures, dimensionality reduction methods, and machine learning techniques in forecasting seizures was investigated.

Results:

All sets of features, dimensionality reduction, and machine learning techniques investigated showed some potential capability to forecast seizures, but SVM and RF machine learning classifiers performed consistently better than ANN.All feature sets tested produced forecasting results greater than chance in all five canines studied with some combinationof dimensionality reduction and machine learning algorithms. Preictal changes in mean and variance PIB, TMCO, SPCOmetrics as well as low gamma (30-55 Hz) and high gamma (65-100 Hz) were observed in multiple canines and occurred as early as 40 minutes before seizures, and may provide insight into the timing and duration of underlying physiologicalchanges leading preceding seizures.

In addition, subject-specific neurophysiological changes in multiple derived features were observed preceding lead seizures, providing some evidence supporting the existence of a distinct, identifiable preictal state.

Conclusions:

These results demonstrate changes in a number of iEEG features prior to seizures and support the concept of a distinct, measurable, pre-ictal (preseizure) state that has an increased probability of seizure occurrence. The existence of a pre-ictal state raises the possibility of clinically relevant seizure forecasting. The current study did not evaluate extended periods of interictal iEEG, and as such we are not able to define the actual specificity of a forecasting algorithm that could be achieved with our approach. In the future we will explore promising features and classifiers applied to continuous long term datasets in an effort to evaluate the potential of clinically viable seizure forecasting.

Funding: NIH NINDS grants UH2-NS95495 and R01-NS92882.

Title: Seizure Forecasting and the Preictal State in Canine Epilepsy

Authors:

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MNS 104 Minnesota Neuromodulation Symposium, April 2016

Title: How and where do neurons mediate visual perceptual learning?: V4 and Shape Detection in Non-human Primates

Authors: Elisabeth J. Moore1, Katherine Weiner1, Geoffrey M. Ghose1

Affiliations:1. Department of Neuroscience, Center for Magnetic Resonance Research, University of Minnesota,Minneapolis, MN 55455

Background:Learning a new ability requires a change in the representations present in cerebral cortex. Understanding where and how neurons change in their ability to encode stimuli during learning, and how introducedmanipulations change this, is relevant to developing neuromodulatory therapies in relation to learningdisorders, as well as to improving computer vision technologies. Visual perceptual training is a useful paradigm for studying learning, as neurons within the visual system can be quantitatively characterized. V4is an intermediate visual area with quantifiable receptive fields that integrates low-level visual inputs, andcontains neurons sensitive to specific curvatures and shapes, which are the basis for perceiving objects.However, whether learning to detect, and correctly identify, shapes occurs in V4 is unknown. Simple shapelearning could be mediated by V4 shape tuned neurons, or may require changes in higher-level objecttuned areas. However, based on preliminary data, we hypothesize that V4 neurons reflect both the visualstimulus and behavioral choice in a shape detection task, and are sufficient for associated performanceimprovements.

MethodsWe recorded in V4 from a 96-electrode array, while two non-human primates learned a shape detectiontask1,2

. Behavioral reliability (performance) improved during training for both animals, indicating learning. LFPinformation was computed in varying windows of time, at varying delays since sensory (stimulusappearance) or behavioral choice event.

ResultsWe found that specific, small numbers of electrodes can predict behavioral timing and reliability. Thissuggests that V4 plays a critical role in shape detection and that performance improvements can be explained by changes within local populations of V4 neurons. To conclusively establish this, we pairedmicrostimulation in V4 with visual training to improve learning outcomes. We found that lasting performance changes are possible, but that the sign of the change depends upon small variations in thespatial and temporal distribution of microstimulation delivered.

ConclusionsPreliminary work suggests that V4 is critical to both stimulus detection and decision making during shape learning. We plan to expand on this with two more animals, by comparing shapes with varying training and stimulation histories, and analyzing precise behavioral strategy differences. We will use fMRI,electrophysiology, and stimulation to determine if V4 is not only involved, but also sufficient for shapelearning, and how these changes occur at varying temporal and spatial scales. These experiments willimprove our understanding of how visual neurons change to encode relevant information over time, and how neuromodulation can be used to alter learning.

References

1. Weiner KF and Ghose GM. Rapid shape detection signals in area V4. Frontiers in Neuroscience. 2014Sep 16; 8:294.

2. Weiner KF and Ghose GM. Population coding in area V4 during rapid shape detections. Journal ofNeurophysiology. 2015 March 18; 113: 3021-3034.

FundingNSF DGE-1069104, P30-NS057091 , R01-EY014989

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Title: Renal denervation normalizes blood pressure and improves glucose metabolism in obese genetically hypertensive Schlager mice

Authors: Ninitha Asirvatham-Jeyaraj1, Christopher T. Banek1, Ruijun Han1, Maria Razzoli1, Brandon J. Burbach2, Alessandro Bartolomucci1, Yoji Shimizu2 and John W. Osborn1

Affiliations: 1. Department of Integrative Biology and Physiology, University of Minnesota, USA; 2. Center for Immunology, Department of Laboratory Medicine and Pathology, University ofMinnesota, USA.

Background: Renal nerve ablation has been reported to decrease arterial pressure and improve glucose metabolism in drug-resistant hypertensive humans, the majority of who are overweight or obese1. However, the mechanism mediating these responses is unknown. The Schlager mouse (BPH/2J) is a genetically inbred strain that has chronically elevated sympathetic activity and mean arterial pressure (MAP) 2. We used this model to assess the effect of renal denervation (RNDX) on MAP and glucose metabolism in lean and obese BPH/2J mice. In addition, since both obesity and renal efferent nerves have been shown to drive renal inflammation3, we also assessed the effect of RDNX on markers of renal inflammation.

Methods: Hypertensive BPH/2J and normotensive BPN mice were maintained on either a low fat (LFD; 10 KCal% from fat) or a high fat (HFD; 45 KCal% from fat) diet for 10 weeks. Radiotelemeters were then implanted for measurement MAP.

Results: MAP was significantly higher in LFD BPH/2J mice (128 ± 2 mmHg) than the LFD BPN controls (107 ± 2 mmHg). Surprisingly, 10 weeks of HFD had no effect on MAP in either strain. MAP was normalized in HFD BPH/2J mice two weeks following RDNX, (~110 mmHg). In contrast, RDNX had no effect on MAP in LFD BPH/2J mice (~134 mmHg). Glucose handling was assessed by glucose tolerance tests three weeks after RDNX/Sham surgery. Glucose tolerance, as quantified by the area under the curve, was impaired to a similar extent in LFD and HFD BPH/2J mice. Moreover, RDNX improved glucose metabolism in both the LFD and HFD groups. Real time PCR was used to determine expression of MCP-1 (monocyte chemoattractant protein-1), a chemokine that recruits monocyte and macrophages to the site of injury, and the pro-inflammatory renal cytokine, tumor necrosis factor alpha (TNFα). In both LF and HF fed groups MCP-1 (135 ± 37.8 fold) and TNFα expression (56.9 ± 1.9 fold) were elevated in BPH/2J mice compared to normotensive BPN controls (2-4 fold). Results indicate that RDNX may reduce MCP-1 expression (to 34.1 fold) in BPH/2J mice but have no effect on TNFα.

Conclusions: These results suggest that renal denervation (RDNX) is effective in the normalization of mean arterial pressure and improve glucose metabolism in obese genetically hypertensive mice. RDNX also lowers chemokines that recruit inflammatory cells to the kidney. Future studies will focus on the assessing the affect of inflammatory cells on renal nerves and their role in driving increase blood pressure or altered glucose metabolism. This will possibly help us develop new therapy for resistant hypertension and diabetes.

References: 1. Mahfoud F et al., Circulation. 2011 May 10;123(18):1940-6,2. Davern PJ et al., Hypertension. 2009 Oct; 54(4): 852-9.3. Xiao L et al., Cir Research. 2015 Aug 28; 117(6):547-57.

Funding: R01 HL116476 and R01 HL0677357

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Title: Neuromodulatory effects of auditory training on audiovisual speech perception in hearing aid users:A functional Magnetic Resonance Imaging study

Authors: Luodi Yu1, Aparna Rao2, Yang Zhang1, Phillip C. Burton1, Dania Rishiq3, Harvey Abrams4

Affiliations:1. University of Minnesota, Twin-Cities, MN, USA; 2. Arizona State University, AZ, USA; 3. MayoClinic, FL, USA; 4. Starkey Hearing Technologies, MN, USA.

Background:This event-related fMRI study investigated neuromodulatory changes in terms of brain activity andfunctional connectivity in hearing aid users with and without auditory training. Our experimental protocol relied on the well-known McGurk effect of hearing /da/ from visual articulation of /ga/ dubbed with the /ba/ sound. Previous research has shown stronger connectivity between areas for multimodal integration(i.e., superior temporal sulcus, STS) and unimodal regions (Nath et al., 2012) in McGurk perceivers thannon-perceivers.

MethodsParticipants in our preliminary study were two adults with moderate hearing loss who were first-timehearing aid users. A structured auditory training program, ReadMyQuips™ (RMQ), was applied,targeting audiovisual speech perception. After 4 weeks of hearing aid use, the experimental participant received RMQ training for 4 weeks. The control participant used hearing aids for 8 weeks and did not receive the training. Identical fMRI tests were administered at pre-fitting and post-training to assesseffects related to hearing aid use with or without RMQ training. An independent functional localizer wasused to identify unimodal regions of interest (ROIs) including voxels within auditory and visual cortex,and a multimodal ROI within posterior STS.

ResultsThe trained experimental participant showed increased activity within the auditory ROI from pretest to posttest, whereas the control remained the same. Both trained and untrained participants showedincreased activity within the multimodal ROI (STS), indicating acclimation to hearing aid use. Enhanced connectivity between the unimodal ROI and multimodal ROI was observed at posttest compared to pretest in both participants, with greater magnitude of change observed in the trained experimental participant.

ConclusionsThe results show initial evidence of facilitation for audiovisual speech perception from hearing aid usewith additional benefit from the RMQ training program. The observable neuromodulatory effects in adultbrain may serve as a useful marker for product design and evaluation.

ReferencesNath, A. R. & Beauchamp, M. S. (2012). A neural basis for interindividual differences in the McGurkeffect, a multisensory speech illusion, Neuroimage, 59(1), 781-787. doi: 10.1016/j.neuroimage.2011.07.024

FundingThis work is funded by Starkey Hearing Technologies.

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Source Imaging of Brain Activation by Low-intensity Transcranial Focused UltrasoundKai Yu1, Abbas Sohrabpour1, Bin He1,2

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Institute for Engineering in Medicine,University of Minnesota, USA

Background: Low-intensity transcranial focused ultrasound (tFUS) has been introduced as a noninvasiveneuromodulation technique with excellent spatial selectivity [1]. However, there is an unanswered question whetherlow-intensity tFUS (much lower than FDA’s regulations) can induce EEG responses over the scalp. We report ourexperimental study to noninvasively detect and localize brain activity from scalp EEG following low-intensity tFUSin an in vivo animal model.

Methods: A single-element focused ultrasound transducer, working in a pulse burst mode, was used to generate tFUSwith a variety of low intensities (Ispta<50 mW/cm2, Isppa<400 mW/cm2) and sonication durations (SD: 5, 50 and 200ms). Up to 16-channel scalp EEG was used to record tFUS-induced brain activation at multiple selected sites in an invivo rat model. Sonication event related potentials (sERPs) were analyzed in time, frequency, and spatial domains.Current source distributions were estimated by means of the electrophysiological source imaging (ESI) [2] toreconstruct spatio-temporal distributions of brain activation induced by tFUS. Regarding the safety concern, theultrasound-induced thermal effect was also numerically evaluated [3].

Results: We found that with increasing intensities of tFUS, the time integral of the mean global field potential fromthe EEG recording within the sonication duration demonstrates an increasing trend; using the same intensity butdifferent sonication durations, the brain also presents different responses to each duration of tFUS. Moreover, whencomparing the sERPs to those by an ultrasound sham condition, significant neuronal activation was observed in time-frequency analysis. Further, ESI revealed initial focal activation in cortical area corresponding to tFUS stimulationsite, and propagated activation to surrounding areas over time.

Conclusions: Our results in this pilot study demonstrate the feasibility of noninvasively recording brainelectrophysiological response in vivo following low-intensity tFUS stimulation, and the feasibility of imaging spatio-temporal distributions of brain activation as induced by tFUS in vivo.References:[1] W. Legon, T. F. Sato, A. Opitz, J. Mueller, A. Barbour, A. Williams, and W. J. Tyler, "Transcranial focused ultrasound modulates theactivity of primary somatosensory cortex in humans," Nat Neurosci, vol. 17, pp. 322-9, 2014.[2] B. He, L. Yang, C. Wilke, and H. Yuan, "Electrophysiological imaging of brain activity and connectivity-challenges andopportunities," IEEE Trans Biomed Eng, vol. 58, pp. 1918-31, 2011.[3] Y. Tufail, A. Yoshihiro, S. Pati, M. M. Li, and W. J. Tyler, "Ultrasonic neuromodulation by brain stimulation with transcranialultrasound," Nat Protoc, vol. 6, pp. 1453-70, 2011.

Funding: This work was supported in part by NSF CBET-1450956. K. Yu was partially supported by a UMN/MnDRIVE GraduateResearch Fellowship.

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Title: Dopamine release in the nonhuman primate caudate and putamen depends upon site of stimulation in the subthalamic nucleus

Authors: Hoon-Ki Min,1,2,3,* Erika K. Ross,1,* Hang Joon Jo,1 Shinho Cho,1 Megan L. Settell,1 Ju Ho Jeong,1,4 Penelope S.Duffy,1 Su-Youne Chang,1,2 Kevin E. Bennet,1,5 Charles D. Blaha,1 and Kendall H. Lee1,2,**

Affiliations:

1. Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA2. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, 55905, USA3. Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA4. Department of Neurosurgery, Dongguk University Gyeongju Hospital, Gyeongbuk, Korea5. Division of Engineering, Mayo Clinic, Rochester, MN, 55905, USA

*These authors contributed equally**Correspondence should be addressed to Kendall H. Lee, MD, PhD, Mayo Clinic, 200 First Street SW Rochester, MN 55905,USA. E-mail: [email protected]

Background:Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for medically refractory Parkinson'sdisease. Although it has recognized clinical utility, its biologic mechanisms are not fully understood, and dopamine release as apotential factor in those mechanisms is in dispute [1]. We tested the hypothesis that STN DBS-evoked dopamine release depends on the precise location of the stimulation site in the STN [2] and site of recording in the caudate and putamen.

MethodsWe conducted DBS with miniature, scaled-to-animal size, multi-contact electrodes and used fMRI to identify the optimaldopamine recording site in the brains of nonhuman primates (n=3) [3], which are highly representative of human brain anatomy and circuitry. Real-time stimulation-evoked dopamine release was monitored using in vivo fast scan cyclic voltammetry.

ResultsWe found that the magnitude of STN DBS-evoked extracellular dopamine release in the caudate and putamen was dependent onthe locus of the stimulation site in the STN and the fMRI identified recording sites in the caudate and the putamen.

ConclusionsWe have demonstrated that DBS coincides with changes in dopamine neurotransmitter release in the basal ganglia. Here we havemapped specific relationship between DBS and changes in neurochemical activity. Importantly, this study shows that DBS-evoked dopamine release can be minimized or maximized through subtle changes in the stimulation site.

References1. Abosch A, Kapur S, Lang AE, Hussey D, Sime E, Miyasaki J, Houle S, Lozano AM (2003) Stimulation of the subthalamicnucleus in Parkinson's disease does not produce striatal dopamine release. Neurosurgery 53:1095-1102; discussion 1102-1095.2. Starr PA, Christine CW, Theodosopoulos PV, Lindsey N, Byrd D, Mosley A, Marks WJ, Jr. (2002) Implantation of deep brainstimulators into the subthalamic nucleus: technical approach and magnetic resonance imaging-verified lead locations. JNeurosurg 97:370-387.3. Min HK, Ross EK, Lee KH, Dennis K, Han SR, Jeong JH, Marsh MP, Striemer B, Felmlee JP, Lujan JL, Goerss S, Duffy PS,Blaha CD, Chang SY, Bennet KE (2014) Subthalamic nucleus deep brain400 word limit (includes Background, Methods, Results, and Conclusions). Underline name of presentingauthor. Do not indent paragraphs - instead, include 2 carriage returns (one blank line) betweenparagraphs. One figure or table can be included.stimulation induces motor network BOLD activation: use of a high precision MRI guided stereotactic system for nonhumanprimates. Brain Stimul 7:603-607.Funding Support for this work came from the National Institutes of Health (R01 NS 70872 awarded to KHL) and The Grainger Foundation.

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Fig. 1. Classification results of the four right-hand motor imagination tasks at peak overall accuracy. Statistically significant increases in accuracy were observed for flexion and supination, as well as the overall accuracy (∗ 𝑝𝑝 < 0.05) (Flex – flexion, Ext – extension, sup – supination, Pro – pronation).

Decoding natural motor imagination tasks through cortical currents for intuitive brain-computer interface use

Bradley J. Edelman1, Bryan B. Baxter1, Bin He1,2

1. Department of Biomedical Engineering, University of Minnesota, MN, USA; 2. Institute for Engineering inMedicine, University of Minnesota, MN, USA

Background: Electroencephalography (EEG)-based brain-computer interfaces (BCIs) using sensorimotor rhythms have allowed users to successfully control various external devices by imagining different kinesthetic movements [1].However, the low spatial resolution of EEG restricts useable motor imaginations (MI) to those which are often cognitively disconnected from the translated action of the output device. Therefore, in order to drive these systems towards more natural use, we attempted to decode MI EEG of common daily actions, including flexion, extension, supination, and pronation of the right hand. We hypothesize that EEG source imaging (ESI) will increase the discriminability of these signals compared to traditional sensor-based approaches.

Methods: Five subjects participated in this study in accordance with a protocol approved by the University of Minnesota IRB. Subjects were instructed to perform 2 Hz self-paced MI of one of the aforementioned tasks in a predefined trial structure while we recorded 64-channel scalp EEG. Initially, data from all tasks were compiled into a single data set. Independent component analysis and ESI mapping were then used to identify a cortical region of interest (ROI) containing the overlapping right-hand task activity. In a parallel analysis, the time course of each individual task EEG was projected onto a cortical model using the weighted minimum-norm estimate [2,3] in order to transform the scalp time series into a whole-brain time series. A time-frequency representation (TFR) was computed for all scalp sensors and dipoles located within the defined ROI using a Morlet wavelet approach and were subsequently split into different frequency bands and time windows for classification.

Results: As seen in Fig. 1, the maximum group-level four-class classification accuracy achieved by the sensor-based and source-based method was 69.5% and 82.2%, respectively. Additionally, the proposed source-based method outperformed the sensor-basedapproach for each of the four individual tasks, with an enhancement ranging between 6.6% and 18.6%. Furthermore, when examining the classifier weights in the spatial source domain, we observed distinct cortical representations of the four right-hand MI tasks that support a functional somatotopic encoding of the primary sensorimotor cortex.

Conclusions: The results of this study indicate that MI tasks involving natural hand manipulations can be decoded with high accuracy using ESI techniques. The successful integration of these tasks in an online source-based BCI may help subjects suffering from various neurological disorders perform useful everyday tasks and improve their quality of life.References:[1] H. Yuan and B. He, “Brain-computer interfaces using sensorimotor rhythms: Current state and future perspectives,” IEEE Trans.Biomed. Eng., vol. 61, no. 5, pp. 1425–35, May 2014.[2] B. He and L. Ding, “Electrophysiological Neuroimaging,” in Neural Engineering, 2nd ed., B. He, Ed. Boston, MA: Springer US,2013, pp. 499–543.[3] R. D. Pascual-Marqui et al., “Low resolution electromagnetic tomography: A new method for localizing electrical activity in thebrain,” Int. J. Psychophysiol., vol. 18, no. 1, pp. 49–65, Oct. 1994.

Funding: This work was supported in part by NSF DGE-1069104, CBET-1264782, and NIH EB006433.

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The learning effect with respect to channel configuration for online brain-computer interface Jianjun Meng1, Jaron Olsoe1, Gabriel Jacobs1, Shuying Zhang1, Angeliki Beyko2 and Bin He1,2

Department of Biomedical Engineering1, Institute for Engineering in Medicine2, University of Minnesota

Background: Motor imagery based brain-computer interface (BCI) using electroencephalography (EEG) ispromising in control of virtual objects and physical devices [1,2], by decoding users’ movement related intention. The selection of control signals, e.g. the channel configuration, plays a vital role for the learning processes of BCI. Although many offline analyses show that using more channels increases the accuracy of BCI control, no online study, to our knowledge, has been reported to assess the effect of number of channels on EEG based BCI. In the current study, we address the question if more EEG channels will provide better performance and if it does, would this effect persist or saturate?

Methods: 64 channel EEG was acquired using a Neuroscan System. 31 BCI naïve subjects were recruited and randomly assigned into two groups. Five sessions of BCI motor imagery experiments of Left and Right cursor control were performed via either small channel (Fig. 1 a) or multichannel (Fig. 1 b) online decoding. A crossover design, which switches the decoding method between two groups, was used to test each configuration for the last two of five sessions. The common spatial filter (CSP) algorithm was used for multichannel configuration, whereas autoregressive (AR) spectrum algorithm from C3 and C4 spatially filtered by a surface Laplacian was used for the small channel configuration [3]. Later another 8 subjects were recruited to perform five sessions of the same task via small channel configuration but CSP as the decoding algorithm (LAPCSP).

Results: A significantly improved performance is obtained in the multichannel group compared to the small channel group (p = 0.017, Mann-Whitney U-test) at the first session. However, no significant difference is found between the multichannel group and the LAPCSP group. In the following sessions there is no significant difference among groups until the last session of crossover. A crossover design aims to investigate whether BCI learning could be transferred from different training algorithm. The performance of the 4th session when two groups switch decoding algorithms shows slightly improved PVC for both groups compared to 3rd session and implies it can be transferred. When the multichannel group (red line) switched to small channel online decoding for the second crossover session (session 5), there is a significant difference of performance compared to their counterparts (blue line) who switched to multichannel online decoding.

Fig. 1 Experimental channel configuration and results. (a) Small channel configuration by large Laplacian filtering. (b) Multichannel configuration processed by common spatial filtering. (c) Group average and standard error mean (sem) of percent valid correct (PVC) for each configuration across each session. Note that the groups of multichannel and small channel configuration switched over during the crossover sessions.

Conclusions: The experimental results revealed that the multichannel configuration exhibited better performance initially within naïve subjects, however saturated and varied with first three sessions and crossover sessions. In contrast, the small channel configuration displayed a congruent improvement on average across all of three sessions and two crossover sessions, finally performs better than its counterpart. It implies small channel facilitate learning improvement across multiple sessions. References [1] He B, et al.: “Sensorimotor Rhythms based Noninvasive Brain-Computer Interfaces,” Proceedings of the IEEE, 103(6): 907-925, 2015.[2] He B, Gao S, Yuan H, Wolpaw J: “Brain-Computer Interface,” In He B (Ed): Neural Engineering, Springer, pp. 87-151, 2013.[3] Meng J, et al.: Biomedical Engineering, IEEE Transactions on, 62(1), 227-240, 2015.Funding: This work was supported in part by the NSF CBET-1264782 and NIH EB006433.

(b) (a) (c)

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Title: Towards a Closed-Loop Deep Brain Stimulation Treatment for Essential TremorAuthors: Enrico Opri1, Jonathan Shute1, Rene Molina2, Kelly Foote3, Michael Okun3, Aysegul Gunduz1,2,3

Affiliations: 1. J. Crayton Pruitt Department of Biomedical Engineering; 2. Department of Electrical Engineering; 3. Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL

Background: Essential Tremor (ET) is one of the most common motor disorders (1), characterized by the presence of a rhythmical, involuntary oscillatory movement of the limbs. Intention Tremor occurs mostly in the upper limbs, typically with slow oscillations (~5-10 Hz) triggered during initiation and execution of goal-directed reaching motions. Although the pathophysiological basis of ET remains unknown, a pathological synchronous oscillation in a neuronal network involving the thalamus, especially the ventral intermediate nucleus (Vim), the premotor (PM) and primary motor (M1) cortices, and the cerebellum has been suggested. It is assumed that deep brain stimulation (DBS) suppresses tremor by masking the “tremor cells” in the Vim that synchronously discharge with oscillatory muscle activity during tremor (2). The goal of this study is to develop a closed-loop brain stimulator that would detect movement intention and presence of tremor as markers to deliver stimulation, avoiding theoretically most of the physiological side effects such as speech and balance difficulties and decreasing the battery depletion of the implant, while delivering an equally effective treatment.

Methods: Patients will be implanted with Medtronic PC+S neurostimulator (Medtronic, Minnesota, USA). This neurostimulator will allow us not only to deliver DBS, but also to record LFP from the same stimulation electrodes. Leveraging the presence of specific biomarkers such as movement intention (mu rhythm on motor, premotor cortices, Vim), presence of tremor (rhythms on Vim, and accelerometer), coherence between electrocorticography (ECoG) and accelerometer, it is possible to responsively deliver DBS and to modulate its stimulation parameters (amplitude, frequency). Preliminary data was collected from patients implanted with PC+S devices and from intraoperative ET cases.

Results: The preliminary analysis executed on intraoperatively collected data from ET patients and on data collected postoperatively from implanted PC+S units shows that is possible to detect volitional movements and tremor neuro-markers to reliably modulate the neurostimulator activation. By using a simple LDA classifier it was possible to detect limb activity bilaterally from a single VIM channel (Figure 1).

Conclusions: Our results suggest that with the use of responsive DBS, completely embedded in the neurostimulator device, it would be feasible to deliver an equally effective treatment while avoiding most of the stimulation side effects such as gait, proprioception and speech impairment, and slowing down the battery depletion of the implant.References:

(1) E. D. Louis and J. J. Ferreira, “How common is the most common adult movement disorder? Update on the worldwideprevalence of essential tremor,” Mov. Disord. Off. J. Mov. Disord. Soc., vol. 25, no. 5, pp. 534–541, Apr. 2010.

(2) J. A. Brodkey, R. R. Tasker, C. Hamani, M. P. McAndrews, J. O. Dostrovsky, and A. M. Lozano, “Tremor cells in the humanthalamus: differences among neurological disorders,” J. Neurosurg., vol. 101, no. 1, pp. 43–47, Jul. 2004.

Funding: University of Florida start-up funds.

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Brain-Context Interactions in Tic Suppression: Description of a New Methodology Integrating rTMS and a Behavioral Experimental Paradigm

Christine Conelea, Ph.D.1,2, Brianna Wellen, B.A.2, Benjamin Greenberg, M.D., Ph.D.1,3

1. Alpert Medical School of Brown University; 2. Bradley Hospital; 3. Butler Hospital

Background: Chronic tics are the most common pediatric movement disorder. Tics occur involuntarily but can temporarily be suppressed. Mechanisms underlying tic suppression are poorly understood but likely involve complex interactions between biological and contextual factors. Unfortunately, integrated methods for studying brain-context interactions in tic suppression are lacking. Neuromodulation offers potential for studying these interactions. Supplementary motor area (SMA) plays a key role in facilitating context-dependent motor output and is hyperactive in those with tics (Orth, 2009). Repetitive transcranial magnetic stimulation (rTMS) over SMA has been explored as a tic treatment (Wu et al., 2014); however, the role of SMA in voluntary tic suppression is unknown. Here we describe an innovative methodology integrating inhibitory rTMS over SMA with a behavioral paradigm designed to measure the effects of context on tic suppression (Woods & Himle, 2004). This methodology enables examination of the role of SMA in tic suppression in various contexts. It is hypothesized SMA inhibition will be associated with decreased tic frequencies and premonitory urges, improved tic suppression, and enhanced suppression in the presence of contingent reinforcement.

Methods: Participants are youth (13-18 years) with chronic tics (n = 30 total; n = 9 enrolled to date). Study components include: 1) clinician-administered diagnostic interviews and self-report measures of tic and psychopathology symptoms; 2) brain MRI, involving bilateral finger-thumb tapping task to highlight SMA; 3) active or sham rTMS over SMA (randomized) coupled with the tic suppression paradigm. During phase 3, participants are covertly videotaped for later coding of tic frequency and urge ratings by coders blind to rTMS status. Active 1hz rTMS is administered in a single 33min train (2000 pulses) at 110% resting motor threshold with a Magstim air-cooled 70mm figure-eight coil positioned over SMA using an MRI-guided neuronavigation platform. Sham rTMS utilizes the Magstim air-cooled sham coil.

Results: Initial efforts suggest that this protocol is acceptable to participants and feasible to conduct. Dependent variables are tic frequency and subjective urge ratings. Since the methodology incorporates a single-subject multielement withdrawal design within a larger group design, results will be examined using both small-n analyses and inferential group statistics to compare dependent variables pre- to post-TMS.

Conclusions: Research on tic suppression mechanisms has historically focused on the separate effects of biology and context despite recognition that brain-context interactions drive symptom expression. Methodological integration of established behavioral experimental paradigms with TMS is a promising strategy for probing tic suppression neurocircuitry within different contexts.

References: Orth, M. (2009). Transcranial magnetic stimulation in Gilles de la Tourette syndrome. Journal of Psychosomatic Research, 67, 591-598. Woods, D. W., & Himle, M. B. (2004). Creating tic suppression: Comparing the effects of verbal instruction to differential reinforcement. Journal of Applied Behavior Analysis, 37, 471-420. Wu, S. W., Maloney, T., Gilbert, D. L., Dixon, S. G., Horn, P. S., Huddleston, D. A.,... & Vannest, J. (2014). Functional MRI-navigated repetitive transcranial magnetic stimulation over supplementary motor area in chronic tic disorders. Brain Stimulation, 7, 212-218.

Funding: NIH/NIMH K23MH103617

32


3D bioprinting conductive nano scaffold with multi-walled carbon nanotubes for improved nerve generation

Se-Jun Lee1, Lijie Grace Zhang1,2 1. Department of Mechanical and Aerospace Engineering, The George Washington University 2. Department ofMedicine, The George Washington University

Background Peripheral nerve defect resulted from various traumas and diseases, represents a critical clinical problem all over the world. A traditional surgical procedure such as nerve autograft is often effective for short-gap, small diameter nerve injuries. However, the repair of more complex defects with larger nerve gap remains problematic. In order to overcome these limitations, synthetic nerve scaffolds are being developed to mimic natural neural extracellular matrix that would encourage neuronal growth and axon elongation across the gap. Nerve scaffolds can be fabricated by various methods. Amongst them, 3D printing techniques have drawn great interest because they can prepare scaffolds with highly controlled spatial architecture and complexity to meet the customized requirements. The main objective of this study is to create an innovative nerve scaffold with a biomimetic nano to micro architecture by integrating advanced 3D printing technique and conductive multi walled carbon nanotubes (MWCNTs). MWCNTs are widely investigated in neural interfacing applications due to its unique physical, chemical and electrical properties. Unlike other conductive polymer materials, their electrical conductivity remains high over a long period of time under harsh condition[1], [2]. It is expected that MWCNT scaffolds may allow the electrical stimulation and promote excitability of neurons. Methods A series of mixture solutions of 0.01%, 0.025%, and 0.05% amine-functionalized MWCNTs and biocompatible poly (ethylene glycol) diacrylate (PEG-DA) hydrogel were successfully printed by our custom made stereolithograpy (SL) 3D bioprinter. SL printed scaffolds were designed as square pattern with small, medium, and large pores geometry (corresponding to 31%, 52%, 66% porosity) using computer aided design software. Neural stem cells (NSCs, ATCC) were further seeded onto prewetted scaffold and evaluated for adhesion and proliferation study.

Results Our results shows that the MWCNTs were homogenously distributed inside the 3D printed scaffolds. 4-hour cell adhesion study showed the scaffolds with 52% porosity can significantly improve cell attachment compared to scaffolds with smaller pores. Then three more groups of scaffolds (52% porosity) with different concentration of MWCNTs were evaluated for proliferation study. Compared to any other groups, NSCs proliferate significantly on scaffolds with 0.01% MWCNTs after 5 day of culture. Figure 1 summarizes the preparation of 3D printed scaffold and interaction with neural stem cells. Conclusions Through this study, amine-functionalized MWCNTs were effectively 3D bioprinted into a novel neural scaffold and greatly improved neural stem cell adhesion and proliferation, thus promising for future neural regeneration applications.

Funding We would like to thank March of Dimes Foundation’s Gene Discovery and Translational Research Grant for financial support.

References

[1] A. Abarrategi, M. C. Gutierrez, C. Moreno- Vicente, M. J. Hortigüela, V. Ramos, J. L. Lopez- Lacomba, M. L. Ferrer, and F. delMonte, “Multiwall carbon nanotube scaffolds for tissue engineering purposes,” Biomaterials, vol. 29, no. 1, pp. 94–102, Jan. 2008.

[2] B. S. Harrison and A. Atala, “Carbon nanotube applications for tissue engineering,” Biomaterials, vol. 28, no. 2, pp.344–353, Jan. 2007.

Fig. 1. A flow chart of 3D printing neural scaffold. (A) Computer-aided design (CAD) model of scaffold, (B) sterolithography for scaffold fabrication and (C) neural differentiation in 3D printed scaffolds.

33


The inhibition function of responsive stimulation on penicillin induced absence epilepsy in ratsYechao Han1,2, Kedi Xu1,2, Xiaoxiang Zheng1,2

1.Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou 310027, China;2.Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Education Ministry,Zhejiang University

Background: Absence epilepsy, which arises from the dysfunction of thalamus and somatosensory cortex, is a disease prevalent in children and juveniles. Some drug-resistant patients could not receive surgery strategy, while avoiding serious complications on nervous system. Therefore, neuromodulation strategies, such as electrical stimulation and optogenentics intervention, become potential choices in the future treatment of absence epilepsy.

Methods: In this study, two strategies of neuromodulation were selectively applied to control the onset of seizures in penicillin-induced absence epilepsy.

1.Responsive Electrical Stimulation: Male Sprague-Dawley rats, anesthetized with isoflurane, were stereotacticallyinjected with penicillin (300UI, 1.785μL) through cannula into right somatosensory cortex. Responsive electricalstimulation (130Hz, 80-120μA, 0.4-0.8ms width, 2-4s) was randomly applied on the right somatosensory cortexaccording to visual detection of seizures.

2.Responsive Optogenentic intervention: To express the opsin, virus (rAAV- CamKIIα-eNpHR3.0-eYPF, 1μL,2.5×1012 copies per milliliter) was injected into right ventrobasal thalamus (AP= -2.8mm, ML= -3.0mm, DV= -6.3mm,) of Sprague-Dawley rats. Four weeks after transfection of eNpHR, absence epilepsy was induced bypenicillin administration in right sensory cortex. Responsive yellow laser stimulation (589nm, 23±3mW) wasrandomly delivered into the thalamus by visual detection.

Results: Responsive electrical stimulation of somatosensory cortex significantly reduced the duration of seizures, compared with no therapeutic stimulation conditions (Stimulation-on: 13.5±1.3s; Stimulation-off: 20.3±2.4s ). When optogenetic modulation of thalamocortical neurons was applied, yellow laser illumination significantly reduced the spike firing rate, changed Multi-Unit Activity (MUA) and deflected Local Field Potential (LFP) of ventrobasal thalamus under penicillin-free conditions. However, after the induction of absence epilepsy, selective inhibition of eNpHR-transduced neurons could not change the LFP and MUA in thalamus. Optogenetic intervention did not increase or decrease the duration of penicillin-induced seizures (Laser-on: 15.0±4.1s; Laser-off: 15.6±3.5s)[1].

Conclusions: Responsive neurostimulation of sensory cortex effectively suppressed absence epilepsy. It avoided many side-effects of current therapy and provided an illuminating solution for the clinical treatment of intricate absence epilepsy. Though optogenetic modulation of thalamus was proved sufficient to control the epilepsy after cortical lesions[2], in this study direct arrest of thalamocortical neurons did not sufficiently suppressed seizures. It could be relevant to the limited range of optogenetic modulation in thalamus and the complicated characteristics of penicillin epilepsy model.References:

[1] Han Y, Ma F, Li H, et al. Optogenetic control of thalamus as a tool for interrupting penicillin induced seizures[C]. IEEE, 2015.

[2] Paz J T, Davidson T J, Frechette E S, et al. Closed-loop optogenetic control of thalamus as a tool for interrupting seizures aftercortical injury[J]. Nature Neuroscience. 2013, 16(1): 64-70.

Funding: This research was supported by the National Natural Science Foundation of China (61305145) and the Specialized Research Fund for the Doctoral Program of Higher Education (20130101120166).

34


Integration of transcranial direct current stimulation and electroencephalography for the study of binocular rivalry

Abhrajeet Roy1, Bradley Edelman1, Angeliki Beyko1, Sheng He2, Steve Engel2, Bin He1, 3

1. Department of Biomedical Engineering, University of Minnesota; 2. Department of Psychology,University of Minnesota; 3. Institute for Engineering in Medicine, University of Minnesota

Background: Binocular rivalry is a perceptual phenomenon in which one’s visual awareness spontaneously shifts between two different images that are presented separately, one to each eye. By elucidating the mechanisms of these stochastic fluctuations in perception, we can potentially learn much about the neural correlates of conscious awareness. Our group has previously identified strong hemodynamic activity in the right posterior parietal cortex (rPPC) during binocular rivalry, using multimodal functional imaging methods [1]. The goal of this study was to investigate the electrophysiological and behavioral effects of electrically modulating activity in the right posterior parietal cortex during ongoing binocular rivalry.

Methods: We successfully obtained 64-channel electroencephalography (EEG) data before, during and after the administration of high definition anodal transcranial direct current stimulation (HD-tDCS) over the rPPC in a group of healthy human subjects engaged in binocular rivalry. 15 subjects came in for two experimental sessions separated by at least one week, with 2.0 mA HD-tDCS being applied over the rPPC for 20 minutes in one session, and sham stimulation being applied for 20 minutes in the other session. The order of sessions was randomized to focus on subject-specific and day-specific responses to anodal HD-tDCS over the rPPC. Following experimentation, spectral analysis was carried out to assess frequency-specific changes in rivalry-related brain activity induced by modulation of the rPPC. Changes in subject behavioral indices were also assessed for comparison with EEG biomarkers of binocular rivalry.

Results: No significant differences in perceptual dominance duration times were found comparing rivalry behavior before, during and after administration of anodal HD-tDCS over the rPPC. For the sham condition, a slight decrease in the average dominance duration time was observed during and after the 20 minute sham stimulation period. Spectral analysis revealed frequency-specific effects of HD-tDCS around perceptual transition times, particularly in the alpha, beta and gamma bands.

Conclusions: To the best of our knowledge, this is the first study to investigate the neural mechanisms of binocular rivalry using integrated tDCS-EEG techniques. Overall, we found a marginal behavioral effect of anodal HD-tDCS over the rPPC, with respect to dominance duration times. However, spectral analysis revealed more subtle, frequency-specific effects of tDCS related to perceptual transitions during continuous binocular rivalry. This study highlights the promise of integrating neuromodulation with EEG for delineating the neural correlates of binocular rivalry and paves the way for future applications of noninvasive neuromodulation for the study of human cognition and behavior.

References[1] Jamison, Keith W., Abhrajeet V. Roy, Sheng He, Stephen A. Engel, and Bin He. 2015. “SSVEP Signatures of BinocularRivalry during Simultaneous EEG and fMRI.” Journal of Neuroscience Methods, January. doi:10.1016/j.jneumeth.2015.01.024.

Funding: NIH R01 EY023101, 2T32 EB008389-06A1, NSF CBET-1264782.

35


(a) (b) (c)

Soft Drink Effects on Sensorimotor Rhythm Brain Computer Interface Performance and Resting-State Spectral Power

John Mundahl1, Jianjun Meng1, Jeffrey He2 and Bin He1,3

1. Dept. of Biomedical Engineering, University of Minnesota, USA; 2. Mounds View High School, USA; 3.Institute for Engineering in Medicine, University of Minnesota, USA

Background: Research has shown that brain-computer interfaces (BCI) based on sensorimotor rhythms can be affected by mind-body awareness, fatigue, and other factors [1, 2]. Since caffeine has been shown to modulate resting state EEG frequency power, and soft drinks represent a substantial portion of caffeine intake, this work aims to study the effect of soft drinks on resting state EEG and BCI performance [3].

Methods: Eight healthy volunteers (7 male, ages 18-25) participated in three 64-channel electroencephalography (EEG) sessions. Each session started and ended with two runs of a Left-Right 1D cursor task. Control signal was the difference between 12 Hz spectral amplitudes from the C3 and C4 motor cortex electrodes. Subjects used right hand and left hand imagined movements to move the cursor to a target on the right or left side of the display, respectively. Then subjects blindly drank a 12 ounce Coca-Cola with either caffeine, sugar, or neither substance (control). The drink selected for each session was randomized to use all drink order permutations. Then 32 minutes of resting state data were collected while alternating between eyes open and eyes closed for two minutes segments.

Results: Alpha (8-12 Hz) and beta (13-30 Hz) power for C3+C4 and all electrodes (global) are shown in Fig. 1a.Caffeine power values are lower than control values across all variables. Sugar power values are most similar to the control values, but occasionally decrease to the caffeine range. BCI performance increases slightly after caffeine and control drinks (Fig. 1b). Sugary drinks decrease average PVC and cause the largest standard deviation. Caffeine consumption shows slightly higher improvement of PVC than the control, while the sugar consumption leads to a decrease of PVC (Fig. 1c). Caffeine consumption also causes the smallest deviation among drinks, while the sugary drink mostly decreases the PVC.

Figure 1. (a) C3 & C4 and Global alpha (8-12Hz) and beta (13-30Hz) power during rest. (b) LR BCI PVC before and after each drink, error bars are standard deviation. (c) PVC change after drink consumption.

Conclusions: During resting state, the decrease in alpha power due to caffeine is consistent with literature. This power reduction could decrease control signal SNR and BCI performance. Instead, BCI performance is consistent between Caffeine and Control. A reduction in control signal SNR could be compensated by an increase in user focus commonly caused by caffeine. Since their effects are relatively small, soft drink consumption does not have to be controlled if the expected result of experimentation is greater. Soft drinks could improve BCI performance if an ingredient increases resting state power or increases focus without decreasing resting state power.

Acknowledgement: We thank John Chen and Albert You for useful discussions for the resting state EEG study.

References: [1] B. He, S. Gao, H. Yuan, and J.R. Wolpaw, “Brain-Computer Interface (In. He B. (ed),” Neural Engineering Springer, New York, 2013.[2] K. Cassady, A. You, A. Doud, and B. He, “The impact of mind-body awareness training on the early learning of a brain-computerinterface,” Technology, vol. 2, pp. 254-260, 2014.[3] R. Barry, J. Rushby, M. Wallace, A. Clarke, S. Johnstone, and I. Zlojutro, “Caffeine effects on resting-state arousal,” ClinicalNeurophysiology, vol. 116, pp. 2693-2700, 2005.

Funding: This work was supported in part by NSF CBET-1264782.

36


Title: Implanted Brain Computer Interface for Real-Time Cortical Control of Hand Movements in aHuman with Quadriplegia

Authors: Gaurav Sharma1, Nick Annetta1, Dave Friedenberg1, Marcie Bockbrader2, W. Mysiw2, Ali Rezai2,Chad Bouton1,#,

Affiliations: 1. Battelle Memorial Institute, USA; 2. The Ohio State University, USA; #. Current affiliation:Feinstein Institute for Medical Research, USA

Background: The objective of this study was to develop a Neural Bridging Technology (NBT) to bypass nervous system injury from spinal cord injury (SCI) or stroke. The NBT study involves the use of intracortically-recorded signals that are linked in real-time to muscle activation through a neuromuscular electrical stimulation system (NMES) to restore movement in a paralyzed limb.

Methods: The NBT has been successfully demonstrated during a Federal Drug Administration (FDA) andInstitutional Review Board (IRB)-approved study [1]. The study participant is a 24-year old male who sustained aC5/C6 SCI and was implanted with a 96-channel microelectrode array in the primary motor cortex. Waveletdecomposition in conjunction with Support Vector Machine (SVM)-based machine learning algorithms were used for neural signal analysis and decoding. Electrical stimulation to the participant’s forearm was applied through a custom made high-definition neuromuscular stimulation cuff comprising of up to 160 electrodes allowing precisestimulation and control of muscle contractions. Resulting movement types and degrees of flexion/extension wereobserved and recorded.Results: The NBT provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and finger motions with high accuracy. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Fig. 1 shows a snapshot from a functional task where the participant was ableto grasp a bottle, pour its contents (dice) into a jar, grasp a stir stick from another jar, transfer the stir stick without dropping it, and use it tostir the dice in the jar. The task required the participant to evoke different neuromodulation patterns to control the opening of his hand, perform a cylindrical and precision pinch grasps, while simultaneously moving his upper arm.

Conclusions: In this study, for the first time, a human with quadriplegia regained volitional, functional movement through the use of intracortically-recorded signals linked to NMES in real-time. With theuse of our investigational system, our C5/C6 SCI participant gained wrist and finger function consistent with a C7-T1 level of injury. This improvement in function is meaningful for reducing the burden of care in patients with SCI asmost C5 and C6 patients require assistance for activities of daily living, while C7-T1 level patients can live more independently. The NBT has potential applications in the field of BCI-controlled neuromodulation to assist peopleliving with motor disorders or paralysis by bypassing/bridging injured portions of the nervous system.References:1. Bouton C., Shaikhouni A., Annetta N., Bockbrader M., Friedenberg D., Nielson D., Sharma G., Sederberg P., Glenn B., Mysiw J.,

Morgan A., Deogaonkar M., Rezai A., “Restoring Cortical Control of Functional Movement in a Human with Quadriplegia”,Nature, in press.

Funding: The work was supported by internal grants from Battelle Memorial Institute and the Ohio State University.

Figure 1: Snapshot from the grasp-pour-and-stir functional movement task.

37


Title: Renal nerves, renal inflammation and hypertension in deoxycorticosterone acetate (DOCA)-salt hypertension: Who is in the driver’s seat?

Authors: Christopher T. Banek, Jason D. Foss, Dusty A. Van Helden, Ninitha Asirvatham-Jeyaraj, and John W. Osborn

Affiliation: University of Minnesota Medical School, United States

Background: Hypertension (HTN) is the single-greatest risk factor for cardiovascular disease – the leading cause of death worldwide. While the etiology remains debated, an increased sympathetic nerve activity, particularly renal (RSNA), and renal inflammation (INF) are regarded as primary contributors. Recently, targeted renal denervation (RDNx) has emerged as a novel therapy for HTN; however, the mechanisms remain unclear. Efferent RSNA is implicated in trafficking of inflammatory T-cells and chemo/cytokine release. Further, INF mediators are known to activate afferent sympathetic nerves. The present study aimed to elucidate the roles of efferent and afferent renal nerves in renal INF and HTN in the deoxycorticosterone acetate (DOCA)-salt rat model. We hypothesized ablation of afferent renal nerves (A-RDNx) and total renal denervation (T-RDNx) would attenuate the development of HTN equally. Further, we hypothesized T-RDNx would obviate renal INF, while A-RDNx would have no effect.

Methods: Uninephrectomized male Sprague Dawley rats (275-300g) underwent A-RDNx (n=10), T-RDNx (n=10), or Sham (n=10). Following baseline measurements, rats received 100mg DOCA (s.c.) and 0.9% saline to drink for three weeks. Arterial pressure (MAP) and heart rate (HR) were measured by radiotelemetry. Renal T-cells were measured by flow cytometry. Renal INF was further assessed by Luminex immunoassay of the following inflammatory chemo-/cytokines: GRO/KC, MCP-1, TNFα, IL-1β, IL-2, IL-6, and IL-17a. Cardiovascular data were averaged over 24 hours, and analyzed by one-way ANOVA with a Bonferroni post-hoc test (α=.05). Data presented as mean ± SEM.

Results: DOCA increased (*p<.05) MAP, and T-RDNx and A-RDNx ameliorated (#p<.05) the HTN (Control 107±6; *DOCA 132±12; #T-RDNx 111±8; #A-RDNx 117±5mmHg). T-cell infiltration was increased (*p<.05) with DOCA-salt, and prevented (#p<.05) by T-RDNx. Interestingly, though A-RDNx attenuated HTN to the same degree as T-RDNX, no effect on renal T-cell infiltration was observed. Moreover, several renal INF chemo-/cytokines (GRO/KC,MCP-1, IL-2, IL-6) were increased (*p<.05) with DOCA-salt, and decreased (#p<.05) by T-RDNx. A-RDNx alsoattenuated (#p<.05) renal chemo/cytokine tissue content.

Conclusions: DOCA-salt HTN was mitigated by T-RDNx and A-RDNx, equally. Renal INF was prevented by T-RDNx and A-RDNx, while only T-RDNx prevented T-cell infiltration of the kidney. Together, these data suggest T-cell trafficking may be mediated by efferent RSNA, but the HTN and the effect of renal INF may be refereed primarily by afferent RSNA. Indeed, these findings are clinically important in that targeted A-RDNx may be a novel therapy for HTN and renal INF. Further studies are underway to elucidate this intriguing role of renal afferent nerves.

Funding: National Institute of Health 1RO1HL116476-01A1; NIHLBI T32 Training Grant 2T32HL7741-21.

Protocol Day

m

mHg

0 7 14 210

10

20

30

40ControlDOCA (Sham)Total-RDNxAfferent-RDNx

* #

#*

*

24hr MAP Response p<.05 vs. Controlp<.05 vs. DOCA (Sham)

#

*

38


Title: Stimulation amplitude-dependent changes in neuronal activity around a chronically implantedthalamic deep brain stimulation array

Authors: YiZi Xiao1, Matthew D. Johnson1,2

Affiliations:1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Institute for TranslationalNeuroscience, University of Minnesota, USA

Background:There is a strong clinical need for implantable deep brain stimulation (DBS) lead designs that allow forbetter steering of electric fields within the brain, especially in cases where stimulation through amisplaced DBS lead results in low-threshold side-effects. Radially segmented DBS arrays (DBSAs) havepotential to rescue therapy in such cases, but the electrophysiolgical effects of directing current within the brain through these arrays remain relatively unexplored. In this study, we have investigated howstimulation amplitudes affect the firing rate and pattern changes of thalamic neurons around a DBSA.

MethodsA DBSA with 8 rows of 4 radial contacts was implanted in the motor thalamus in a non-human primate.A single row of contacts was selected where each contact performed 3 sets of 100Hz stimulations at350µA, 250µA and 150µA. Microelectrode recordings were made in a grid pattern around the DBSAcollecting 30s of pre-DBS/DBS/post-DBS data. Peri-stimulus time histograms were created for all 3periods. Changes in neuronal responses between the DBS and pre-DBS periods were grouped into ninecategories based on firing pattern modulation (FPM) and change in firing rate. An entropy-based method was used to quantify the degree of FPM and determine instances of significant modulation.

ResultsResults are as follows: (1) 11/85 (12.94%) recorded cells showed significant FPM under DBS. (2): 26%,22% and 19% of all recordings under 350µA, 250µA and 150µA stimulation weresignificantly modulated in some way. (3): Cells that showed firing pattern or rate modulation weresparsely distributed and were not confined to regions in the immediate proximity of the DBSA. (4)However, stimulation amplitude increase induced greater change in firing pattern (i.e. increasedregularity) in the subgroup of cells that showed significant FPM under at least one stimulation amplitude.(5) Interestingly, only 3.25% (±3.8%) of DBS pulses produced a phase-locked spike in cells with asignificant excitatory FPM. DBS also suppressed 81% ± 4.44% of phase-locked spikes for inhibitoryFPMs.

ConclusionsWhile computational models often predict uniform modulation of neuronal spike activity around a DBSlead, this study demonstrates that the volume of neuronal modulation is in fact sparsely represented.Moreover, while neuronal activity becomes time-locked to DBS, only a very small fraction of stimuluspulses actually result in a phase-locked spike. This work will help inform the next generation ofcomputational models of DBS and provide insight for future implant designs.

FundingNIH R01 NS081118

39


Neuronix Enables Continuous, Simultaneous Neural Recording and Electrical Stimulation Anh T. Nguyen, Tong Wu, Jian Xu, and Zhi Yang

University of Minnesota Twin Cities, MN, USA

Background: Electrical stimulation has been used for probing neural circuitry and identifying networks of neurons for more than 200 years. Despite its extensive use, the mechanism of action of electrical stimulation on the nervous system remains poorly understood. It requires concurrently monitoring the neural activity at the same time to investigate of the behavior of neural populations. However, with current electrical stimulation and recording technologies reported in the literature, it is not possible to “talk to the brain” and “hear from the brain” at the same time.

Methods: We make contributions from two aspects, 1) a new technique and device that allows recording and microstimulation at the same time instead of one impeding the other. 2) A new methodology that supports ultra-large-scale recording and precise neuromodulation. We are integrating these innovations into Neuronix, a next generation brain technology. Figure 1 shows a beta version Neuronix that has been validated through in vitro and in vivo experiments.

Results: Neuronix has several advanced features, for example, 1) continuous, full-duplex simultaneous neural recording and stimulation. To the best of our knowledge, no other device available today that can perform such experiments. 2) Fully-integrated scaling strategy where the size of the implantable electronics is not increased with the channel count, allowing ultra-large-scale recording and stimulation. 3) A new design that could suppress electrode noise and has been verified in animal experiments, thus can support high impedance electrodes. This feature is important to ultra-large-scale recording, where each electrode is small, high impedance, and with more noise.

Conclusions: We report a new Neuronix technology that allows continuous, simultaneous neural recording and electrical microstimulation. In vitro and in vivo experiments have been performed and careful analyzed to validate this feature. Neuronix enables bidirectional communication with the brain circuits and new experiments towards a better understanding of the impact of microelectrical stimulation. We envision the technology applies to a wide spectrum of neurological diseases through closed-loop neuromodulation.

Figure 1. A beta version Neuronix validated in animal experiments at the University of Minnesota. Together with research collaborators, we are pushing Neuronix into clinical use. We envision that miniaturized implants will revolutionize health care and disease treatment. For more information, please refer to http://yanglabumn.com/.

Funding: University of Minnesota start-up fund.

40


A case report of visual and motor recovery after cognitive sensorimotor rehabilitation in a patient with cortical blindness

Daniele De Patre1, Franca Panté1, Carla Rizzello1, Marina Zernitz1, Mariam Mansour2, Lara Zordan3, Thomas Zeffiro4, Erin O. Connor5, Teresa Bisson6, Andrea Lupi7, Carlo Perfetti1, Ann Van de Winckel6

1. Centro Studi di Riabilitazione Neurocognitiva Villa Miari, Italy; 2. Unità Operativa di Neuroradiologia di Vicenza,Italy; 3. Unità Operativa Complessa di Neurochirurgia di Vicenza, Italy; 4. Neurometrika, USA; 5. Temple UniversitySchool of Medicine, USA; 6. University of Minnesota, USA; 7. Unità Operativa di Medicina Nucleare di Vicenza, Italy

Background: Spontaneous partial recovery of vision can occur between 1-6 months after onset of cortical blindness. Recent neuroimaging techniques seem to support the potential of visual rehabilitation to modulate brain plasticity over a longer time1. However, to date, no visual rehabilitation technique has been adopted as gold standard1; the clinical outcomes are variable; and rarely translate into improvements in daily life activities (ADL). The main objective of this case study was to determine the neuromodulatory role of cognitive sensorimotor rehabilitation2,3 in a patient with cortical blindness.

Methods: A 48 year old female patient presented with severe cortical blindness and tetraplegia caused by hypoxia after cardiac arrest. The patient distinguished shapes and colors against a light background after 1.5 year of standard visual rehabilitation. She was dependent in ADL. The patient then started cognitive sensorimotor rehabilitation for 8 months, 5 days/week, 3 hours/day. This rehabilitation2,3 consisted of discrimination exercises correlating sensory and visual information to reconstruct vision and improve daily life motor performance. Clinical assessments for arm movements (Motor Evaluation of Upper Extremity in Stroke Patients, MESUPES), activities of daily living (Barthel ADL index) and well-being (Warwick-Edinburgh Mental Wellbeing Scale, WEMWBS), as well as PET imaging were performed before and after cognitive sensorimotor rehabilitation.

Results: Visual performance significantly improved after cognitive sensorimotor rehabilitation: The patient’s field of view increased to 15*10 cm; she recognized and described objects; watched television; used her cell phone; and relearned to read. She improved 45 points (65/100) on the “Barthel ADL index”, reflecting independence in self-care and walking with assistance. She increased 23 points (48/58) on the MESUPES, i.e. she moved her arm accurately and moved her fingers selectively. She improved 23 points (57/70) on the WEMWBS (improving 23 points), i.e. she felt self-reliant. Fig.1. displays the results of the PET images before and after rehabilitation.

Our findings support the feasibility of cognitive sensorimotor rehabilitation to modulate neuroplasticity in preserved regions in primary visual areas. The increased fronto-parietal activations probably relate to the observed clinically improved motor function. Correlating sensory and visual information during this rehabilitation probably activates pathways between visual and sensory areas, thereby possible providing an alternative route to reactivate preserved primary visual areas.

Conclusions: This study provides support for the neuromodulatory role of the cognitive sensorimotor rehabilitation in a patient with cortical blindness, who experienced an impressive clinical visual and motor recovery with marked ADL improvement, more than 2 years after onset. References:1. Pollock A, Hazelton C, Henderson CA, at al. Interventions for visual field defects in patients with stroke. In: Cochrane Study Group,editor. The Cochrane Library. Chichester, UK:Wiley. 2011. p. 1–83.2. Perfetti C, Panté F, Rizzello C, et. al. Il dolore come problema riabilitativo. Padova, Italia: Piccin; 2015.3. Perfetti C. La rieducazione motoria dell’emiplegico. Napoli. Italia: Libreria scientifica già GHEDINI s.r.l. 1979

Funding: No funding

Fig.1. TOP (before cognitive sensorimotor rehabilitation): Axial PET slices showed reduced glucose metabolism in the bilateral extrastriate cortex. BOTTOM (subtraction of PET images before and after rehabilitation superimposed on the patient’s T2-weighted image in MNI space): Focal increases in glucose metabolism were seen bilaterally in the occipital pole (BA 17) in areas showing relatively preserved metabolism prior to rehabilitation. In addition, bilateral metabolic increases were seen in the calcarine cortex, precentral sulcus (dorsal premotor cortex), angulargyrus, and in the left inferior frontal gyrus

41


Spatial Distributions of Subthalamic Oscillations in Parkinson’s Disease During Resting and Movement

Authors: Xinyi Geng1, Xin Xu2, Yongzhi Huang1, Zhipei Ling2, Shouyan Wang1

Affiliations: 1. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, China; 2. General Hospital of PLA, China

Background: The subthalamic nucleus (STN) had been proved to be an efficient stimulating target for Parkinson’s disease (PD). The local field potentials (LFPs) recorded from the STN in patients with PD are characterised bymultiple frequency bands which related with symptoms, medication treatment and the recording locations in subthalamus. This paper aims to determine the distributions of subthalamic oscillations in PD during resting and movement to refine the selection of contacts for deep brain stimulation (DBS).

Methods: Eighteen subjects with PD underwent intraoperative LFPs recording from DBS electrodes during resting and cued involuntary movement task. The LFPs were quantified using spectral and time-frequency analysis. Pairedt-test were used to respectively define oscillatory frequencies with significant changes at response time of movementand post-movement time for each side of recordings. Power of the oscillations were then compared across allrecording channels on each side to illustrate the spatial distributions of the oscillations. Wilcoxon signed-rank testwere applied to compare the distributions of oscillations between resting and movement.

Results: Subthalamic oscillations were significantly modulated by movement in five time-frequency ranges whichwere around 3-10Hz, 10-33Hz and 55-80Hz at the response time of movement and 3-10Hz and 10-33Hz at post-movement time. Power around 3-10Hz increased at the response and decrease at post-movement. Movement modulations around 3-10Hz distributed with no significant difference both at response and post-movement comparedto rest (p=0.4613; p=0.047). Movement modulated oscillations around 10-33Hz desynchronized at the response time and rebound back after movement. These modulations locate equally at response and post-movement time andsignificantly dorsally to the location of resting oscillation (p=0.0024). Also, the power increases around 65-85Hz were significantly dorsally distributed to the relative oscillations at rest (p=0.0003).

Conclusions: The results reveal the spatial distributions of subthalamic oscillations in PD are different at rest andmovement in several frequencies. The findings provide an evidence that the generators of oscillations for different behaviors locate separately in subthalamus. The target of STN located with resting electrophysiological recordings is not the same region with motor functions. These gives a hint that the subthalamic oscillations can be modulatedrespectively with different stimulating contacts and parameters and hence leads to a personalized DBS treatment toimprove different symptoms while avoiding side-effects.

Keywords: Spatial distribution, subthalamic oscillation, Parkinson’s disease.References:

[1] Chen C, Pogosyan A, Zrinzo LU, et al. “Intra-operative recordings of local field potentials can help localize the subthalamic nucleusin Parkinson's disease surgery”. Exp Neurol, 198, pp. 214-221, (2006).[2] Kuhn A A, Williams D, et al. “Event-related beta desynchronisation in human subthalamic nucleus correlates with motorperformance”, Brain, 127, pp. 735-746, (2004).[3] Wang J, Hirschmann J, Elben S, “High-Frequency Oscillations in Parkinson's Disease: Spatial Distribution and Clinical Relevance”.Mov Disord, 29, pp. 1265-1272, (2014).

Funding: Supported by the National Natural Science Foundation of China (81471745).

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Fast mapping of brain electrical properties using MRI – a simulation studyYicun Wang1, Pierre-Francois Van de Moortele2 and Bin He1,3

1. Department of Biomedical Engineering, University of Minnesota; 2. Center for Magnetic ResonanceResearch, University of Minnesota; 3. Institute for Engineering in Medicine, University of Minnesota

Background:

Precision neuromodulation in human brain by electrical or magnetic approaches requires accurate mapping of electrical properties, especially when abnormalities exist, such as a brain tumor. We aim to reconstruct the electrical properties robustly in the brain by solving Maxwell’s equations with acquired 𝐵𝐵𝐵𝐵1 maps from MRI that are in low signal to noise ratio (SNR), which is usually the case when scan time is limited.

Methods:Starting from time-harmonic Maxwell Equations, the central equation corresponding to a brain slice reads

(𝛻𝛻𝛻𝛻2𝐵𝐵𝐵𝐵1+)𝛾𝛾𝛾𝛾𝑐𝑐𝑐𝑐 + �𝜕𝜕𝜕𝜕𝐵𝐵𝐵𝐵1+

𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕− 𝑖𝑖𝑖𝑖

𝜕𝜕𝜕𝜕𝐵𝐵𝐵𝐵1+

𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕��𝜕𝜕𝜕𝜕𝛾𝛾𝛾𝛾𝑐𝑐𝑐𝑐𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕

+ 𝑖𝑖𝑖𝑖𝜕𝜕𝜕𝜕𝛾𝛾𝛾𝛾𝑐𝑐𝑐𝑐𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕

� = −𝜔𝜔𝜔𝜔2𝜇𝜇𝜇𝜇0𝐵𝐵𝐵𝐵1+

where 𝛾𝛾𝛾𝛾𝑐𝑐𝑐𝑐 is the unknown complex-valued parameter related to electrical properties comprising conductivity 𝜎𝜎𝜎𝜎 and relative permittivity 𝜀𝜀𝜀𝜀𝑟𝑟𝑟𝑟; 𝐵𝐵𝐵𝐵1+ is the transmit magnetic field acquired from MRI; 𝜔𝜔𝜔𝜔 is the operating frequency and 𝜇𝜇𝜇𝜇0 is the magnetic permeability of free space. This problem takes form of a partial differential equation (PDE). It can be written as an inverse problem, and solved either in Least-Squares regime only or regularized by sparsity to improve reconstruction accuracy and robustness.

A numerical simulation has been performed to acquire 𝐵𝐵𝐵𝐵1+ maps from a 16-channel transmit-receive array head coil for 7T MRI loaded with a realistic human head model (Duke model, Virtual Family) in Finite Difference Time Domain (FDTD) based software SEMCAD. Independent and identically distributed Gaussian noise was added to the 𝐵𝐵𝐵𝐵1+ maps from 16 individual channels. Electrical properties were reconstructed using Total Variation as the sparsity constrain, and solved by Alternating Direction of Multipliers Method (ADMM).

Results: At low SNR, the Least-Squares reconstruction gives substantially deviated values from target especially in the center of the brain and more severe oscillations due to noise effects, while the proposed Sparsity-Promoting algorithm still preserves the correct contrast between tissues and shows mild noise contamination.

Figure 1. Reconstructed conductivity map of a simulated brain model at SNR=50. Left: reconstruction with Least-Squares method; Right: reconstruction with the proposed Sparsity-Promoting method.

Conclusions: The proposed algorithm is able to provide robust and accurate electrical properties maps at low SNR, which makes it promising for fast brain mapping and modeling to guide neuromodulation therapies.References:[1] J. Liu et al., Magn. Reson. Med. 2015. [2] M. Lustig et al., Magn. Reson. Med. 2007. [3] G. Adriany et al., Magn. Reson. Med. 2008.

Funding:

This work was supported in part by NIH R21EB017069.

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Title: Effect of Renal Denervation and Celiac Ganglionectomy on Mean Arterial Pressure in Hypertensive Schlager (BPH/2J) Mice

Authors: Madeline M. Gauthier1, Ninitha Asirvatham-Jeyaraj1, Claire Breitenstein1, and John W. Osborn1

Affiliations: 1. Department of Integrative Biology and Physiology, University of Minnesota-Twin Cities, USA

Background: Renal denervation (RDNx), a surgical intervention which removes the nerves innervating the kidneys, is known to lower mean arterial pressure (MAP) in patients with high blood pressure. Less well studied is the effect of celiac ganglionectomy (CGx), a procedure where the nerves innervating the splanchnic vascular bed are removed. CGx has proven equally effective at lowering MAP in some animal models.1,2 The mechanism of action of both interventions remains unknown, however evidence suggests that in hypertensive mice, RDNx may affect MAP by preventing the trafficking of inflammatory markers to the kidneys.3 We hypothesized that RDNx and CGx would both lower MAP in genetically hypertensive Schlager (BPH/2J) mice and that this would correlate with a decrease in sympathetic activity and a decrease in proinflammatory cytokines.

Methods: BPH/2J mice underwent radiotelemeter implantation for monitoring of MAP followed by a 7-10 day convalescence period, after which control blood pressure data was collected for 2 days. Next, mice were randomly subjected to one of three treatments: RDNx, CGx, or sham. MAP and heart rate were recorded for 14 days post-operatively. At the conclusion of the study, the mice were euthanized via exsanguination. Tissues were immediately collected and flash-frozen in liquid nitrogen and stored at -80°C for later analysis of both pro- and anti-inflammatory cytokine mRNA levels via qualitative real-time PCR.

Results: In genetically hypertensive Schlager mice, baseline MAP in the three groups was similar (~130mmHg). On post-operative day 14, MAP in both RDNx (-13 ± 2 mmHg) and CGx (-8 ± 0.3 mmHg) decreased, but was not affected in sham controls (-6 +/- 10 mmHg). The change in heart rate (beats/min) was not different between groups 14 days after surgery (-24 ± 4 in sham, -21 ± 33 in RDNx, -41 ± 18 in CGx). RDNx decreased renal mRNA expression of the proinflammatory cytokines interleukin 1 beta and tumor necrosis factor alpha in BPH/2J mice 2 weeks after surgery.

Conclusions: Because RDNx and CGx decreased MAP, we conclude that the both the renal and splanchnic nerves contribute to the high baseline MAP in Schlager mice. Lower expression of proinflammatory cytokines in renal tissue with RDNx suggest a possible link between proinflammatory renal cytokines and mean arterial pressure in Schlager mice. Future studies will explore the direct link between targeted sympathetic ablation, inflammation, and change in mean arterial pressure using this mouse model.

References:1. Foss JD, Fink GD, Osborn JW. Reversal of genetic salt-sensitive hypertension by targeted sympathetic

ablation. Hypertension. 2013;61(4):806-11. doi: 10.1161/HYPERTENSIONAHA.111.00474. Epub2013 Feb 4.

2. King AJ, Osborn JW, Fink GD. Splanchnic Circulation Is a Critical Neural Target in Angiotensin II SaltHypertension in Rats. Hypertension. 2007;50:547-556. doi:10.1161/HYPERTENSIONAHA.107.090696. Epub 2007 July 23.

3. Xiao L, Kirabo A, Wu J, et al. Renal Denervation Prevents Immune Cell Activation and RenalInflammation in Angiotensin II-Induced Hypertension. Circ Res. 2015;117(6):547-57. doi:10.1161/CIRCRESAHA.115.306010. Epub 2015 Jul 8.

Funding: NIH R01-HL 067357-15, R01 HL 116476-02 and University of Minnesota Undergraduate Research Opportunities Program.

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Identifying Optimal Electromyography Responses in Infants with Perinatal Stroke: The Foundation for a Novel Transcranial Magnetic Stimulation Protocol

Chao-Ying Chen1, Mo Chen2, Bernadette Gillick1,3

1. Department of Physical Medicine and Rehabilitation, Medical School, University of Minnesota; 2. University ofMinnesota, Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab; 3. Program of PhysicalTherapy, Rehabilitation Science Program, Department of PM&R, Medical School, University of Minnesota

Background: Little is known about the pattern of resulting brain reorganization that eventually can manifest as cerebral palsy (CP) in infants with perinatal stroke. Thus, the overall purpose of this study is to understand brain reorganization, using transcranial magnetic stimulation (TMS), in infants with perinatal stroke during a critical period of brain and behavioral development, between 3 and 5 months of age. Adapting adult and pediatric TMS research, this study establishes the methodology for an infant-appropriate protocol by considering the infants’ compliance and tolerability. To do so, we need to have an active understanding of electromyography (EMG) responses in the typically developing infant population. This investigation prepares us to conduct our upcoming TMS testing study in infants with perinatal stroke. Specifically we will identify the optimal upper extremity muscle with the most consistent resting EMG activity for reliable TMS testing.

Methods: Two typically developing infants (one male: aged 3 months 12 days; one female: aged 4 months 6 days) visited our lab for EMG observation. The EMG activity of five muscles included the abductor digiti minimi, wrist flexor, wrist extensor, biceps, and triceps were observed in the following three testing conditions: 1) infants can move their arms freely, 2) infants’ arms are constrained to limit wrist flexor, bicep, and triceps contraction, and 3) providing upper extremity traction from supine to sit to facilitate biceps isometric contraction.

Results: All the observed muscles showed resting EMG activity between ±10 and ±20 μV, but the resting EMG activity are varied in duration and frequency. Biceps in the arm-constrained condition and wrist flexor in the free moving condition showed the longest resting EMG activity of ±10 μV (Figure 1).

Conclusions: In our protocol, the delivery of a single TMS pulse is triggered when the resting EMG activity is lower than a pre-defined threshold.1 This threshold will be slightly higher than the resting EMG activity, which is ±10 μV based on our observation. However, the threshold can vary due to electrodes attachment, participant’s skin conductivity character, skin preparation quality, and electrical environment noise level. This method for our protocol integrates the fact that most infants will not consistently and voluntarily remain relaxed in an awake state. The biceps or wrist flexor musculature appear to be the optimal muscles to provide adequate windows of resting EMG activity as the triggering reference to examine brain reorganization using TMS in infants with perinatal stroke.References:1. van de Ruit, M., Perenboom, M.J., and Grey, M.J., TMS brain mapping in less than two minutes. Brain Stimul, 2015. 8(2): p. 231-9.

Funding: University of Minnesota start-up funding (Gillick)

Figure 1. One infant volunteer’s EMG activity of biceps in arm-constrained condition (upper panel) and wrist flexor in free moving condition (lower panel)

Example of timing for delivering TMS (muscle activity of ±10μV)

Example of timing for delivering TMS (muscle activity of ±10μV)

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A comparison of paretic and non-paretic hand electromyographic responses with single-pulse transcranial magnetic stimulation testing in children with congenital hemiparesis. Tonya L. Rich, MA, OTR/L1, Chao-Ying Chen, PhD, PT1, Maíra C. Lixandrão, PT1,2, Bernadette T.

Gillick, PhD, MSPT, PT1, 1. University of Minnesota, Program in Rehabilitation Science, USA 2. Federal University of Sao Carlos,

Department of Physical Therapy, Brazil Background Children with congenital hemiparesis exhibit corticospinal tract re-organization due to atypical brain development secondary to perinatal stroke or periventricular leukomalacia. Transcranial magnetic stimulation (TMS) can be used to identify reorganization patterns in the corticomotor pathway. Evaluation of the magnitude and timing of the motor evoked potential (MEP) produced by single pulse (SP) stimulation of each hemisphere, thereby establishes contralesional, lesional, or bi-hemispheric control of the paretic hand.1 Re-organization patterns may influence MEP responses during TMS testing. We incorporated TMS testing into a clinical trial involving children with congenital hemiparesis to assess cortical excitability.

Methods Eight participants of a transcranial direct current stimulation/constraint-induced movement therapy study (clinicaltrials.gov NCT02250092) completed SP TMS testing. TMS was applied over non-lesional primary motor cortex, using an intensity of 120% resting motor threshold with first dorsal interosseous (FDI) muscle contraction (20 trials). MEP timing (latency), amplitude and cortical silent period (CSP) duration were measured. MEP latency represents time from stimulus artifact to the onset of the MEP. CSP duration was determined by the time from the end of the MEP to the return of EMG activity that exceeds 100% of baseline activity. Motor performance was measured with the Assisting Hand Assessment (AHA) (0-100 logit-based AHA units whereas 100 reflects highest function). Differences between hand strength was measured using dynamometry (e.g. the greater the difference in strength between the hands, the greater the impairment).

Results TMS procedures were well tolerated in all children with no serious adverse events. Lesion locations varied affecting cortical and/or subcortical structures. Investigators would expect electromyographic (EMG) responses only of the contralateral hand to the hemisphere stimulated by TMS. However, ipsilateral MEPs were recorded from EMG electrodes over the FDI muscle of the paretic hand. Table 1 summarizes descriptive data of two children exhibiting differing reorganization patterns with both demonstrating bilateral MEP responses. The neurophysiological and functional strength profiles varied between the two children.

Conclusions Two children of a larger clinical trial demonstrated corticomotor reorganization pattern and bilateral MEP’s. This may reflect contributory pathways to motor control and movement of the upper limb. How this reorganization and affects bimanual hand function warrants further investigation. Table 1. Nonlesioned hemisphere Cortical Silent Period testing in two children with congenital hemiparesis.

Child 1 Child 2 Age 10 years old 10 years old Side of Lesion Right hemisphere Left hemisphere Presence of TMS-Evoked MEP Non-lesioned hemisphere only Bilateral CSP Duration (Nonparetic hand average) 158.55ms 125.75ms MEP Latency (Nonparetic hand average) 14.70ms 12.89ms MEP Latency (Paretic hand average) 19.03ms 17.53ms MEP Amplitude (Paretic hand average) 526.71µV 60.19µV AHA 68 77 Grip Strength Difference Between Hands 36# 17#

CSP: Cortical Silent Period; MEP: Motor Evoked Potential; TMS: Transcranial Magnetic Stimulation; ms: milliseconds. Hand function is measured with the AHA: Assisting Hand Assessment (0-100 Logit-based units) and Grip strength differences (pounds). References 1. Holmstrom L, Vollmer B, Tedroff K, et al. Hand function in relation to brain lesions and corticomotor-projection pattern in children with unilateral cerebral palsy. Developmental Medicine & Child Neurology. 2010;52(2):145-152. Funding NIH/NICHD 5 K01-HD078484-02 (PI: Gillick), Cerebral Palsy Foundation (PI: Gillick), Foundation for Physical Therapy (PI: Gillick), UMN Marie Louise Wales Fellowship (Rich), MnDRIVE (Rich), Sao Paulo Research Foundation (FAPESP) (Lixandrão).

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Title: Transcranial Focused Ultrasound for Primary Motor Cortex Stimulation in HumansAuthors: Leo Ai1, Jerel K. Mueller1, Priya Bansal1, Wynn Legon1

Affiliations: 1. University of Minnesota, USA, Department of Physical Medicine and Rehabilitation

Background: Transcranial focused ultrasound (tFUS) is an emerging form of non-surgical neuromodulation that provides very high spatial resolution on the millimeter scale. tFUS has been successfully used in humans for cortical stimulation of the somatosensory cortex that also demonstrated effects on tactile threshold behavior [1]. Here, we extend these findings to the primary motor cortex (M1) in humans. We tested the effect of tFUS to M1 on the blood oxygen level dependent (BOLD) response, motor cortical excitability and reaction time behavior.

Methods: BOLD data was acquired on a 3T Siemens TIM Trio MRI scanner using a gradient echo echo-planar imaging sequence and an event-related design where 90 0.5s pulsed ultrasound stimuli were delivered every 12-14s targeted over the M1 region. We examined the effect of tFUS on motor cortical excitability using a custom made transcranial ultrasound magnetic stimulation (TUMS) device that allows for concurrent and concentric transcranial magnetic stimulation with tFUS. TUMS was delivered to the dominant M1 first dorsal interosseous (FDI) muscle representation under real and sham conditions to test for an effect on motor evoked potential (MEP) recruitment curves. In addition we tested the effect of tFUS on M1 inhibition and facilitation using a paired-pulse protocol under real and sham tFUS conditions. Finally, we tested the effect of tFUS on reaction time of the FDI muscle by delivering either real or sham tFUS time-locked to a visual stimulus to cue a simple FDI adduction movement.

Results: The MRI study revealed very focal BOLD response in the sensorimotor region in good accordance with the focus of the ultrasound beam in 3 of 6 participants. The TUMS study showed that tFUS increased the response of M1 to TMS, but did not shift the recruitment curves. tFUS also reduced M1 inhibition and increased M1 facilitation during the paired pulse protocol. Finally, tFUS reduced reaction times.

Conclusions: The studies performed indicate that tFUS increases motor cortical excitability through a reduction in inhibition that also leads to a behavioural benefit. BOLD responses in M1 as a result of tFUS are variable and not always detectable. These are encouraging initial results on the effect of tFUS to M1 in humans and with refinement could have important implications in global brain mapping efforts and in many forms of guided therapies in clinical settings.

Reference:[1] W. Legon, T. F. Sato, A. Optiz, J. Mueller, A. Barbour, A. Williams, W.J. Tyler, “Transcranial Focused UltrasoundModulates the Activity of Primary Somatosensory Cortex in Humans,” Nat Neurosci, vol. 17, 2014, pp. 322-3239

47


Title: rTMS and Finger Tracking Training in a Single Subject with Brainstem StrokeAuthors: Kate L. Frost1, Thomas Broback2, Nicole Carlson2, Caitlin Daggett2, Megan Dalbec2, James R.

Carey1,2

Affiliations: 1. Program in Rehabilitation Science, University of Minnesota, USA; 2. Department of Physical Therapy, University of Minnesota, USA

Background: Neuromodulation using repetitive transcranial magnetic stimulation (rTMS) is under investigation in people with stroke. Many studies quantify the efficacy of rTMS by measuring ipsilesional motor evoked potentials (MEPs) with amplitudes ≥50 µV. However, nearly 40% of individuals with stroke do not have an elicitable ipsilesional MEP1,2 and are therefore excluded from most studies. Thus, the efficacy of rTMS in these participants is unknown. This study explores the use of functional magnetic resonance imaging, transcranial magnetic stimulation and motor function tests to quantify the influence of primed rTMS in a single subject with no ipsilesional MEP amplitude ≥50 µV.

Methods: The single human subject (45 year old male, left pons lesion, six years post-stroke) followed a cross-over design with two intervention arms (sham-primed rTMS+tracking and real-primed rTMS+tracking) applied in random order with a one-month washout. Arm 1 included sham 6-Hz priming of sham 1-Hz conditioning rTMS to the contralesional primary motor area (M1) followed by one hour of finger tracking training with the paretic index finger. Arm 2 included real 6-Hz priming of real 1-Hz conditioning rTMS followed by one hour of finger tracking training with the paretic index finger. Outcome measures were laterality index, interhemispheric inhibition (IHI) index, box-and-block score and finger tracking score. A descriptive analysis was used for laterality index and motor function scores because of only one measurement per session. Paired t-tests were used to analyze IHI indices because of 10 measurements per session.

Results: Following sham rTMS+tracking, the laterality index shifted from negative to positive, reflecting greater cortical activation of ipsilesional M1. However, box-and-block score, finger tracking score and IHI indices did not change. Following real rTMS+tracking, the laterality index moved closer to zero, reflecting a trend toward decreasing activation of contralesional M1. IHI increased significantly (p<0.05) in the direction of contralesional to ipsilesional M1, counter to our hypothesis. Box-and-block and finger tracking scores did not change.

Conclusions: Neural activation lateralized from contralesional to ipsilesional M1 following five days of paretic finger tracking without adjunctive rTMS but with no accompanying behavioral improvement, possibly because of the short training time. Including rTMS as an adjunct to behavioral training worsened the IHI affecting ipsilesional M1. The lack of benefit when rTMS was applied as an adjunct to behavioral training is reminiscent of other studies reporting that “one size does not fit all”3 such that contralesional rTMS should not be included in the absence of an ipsilesional MEP.References:1. Escudero J, Sancho J, Bautista D, Escudero M, Lopez-Trigo J. Prognostic Value of Motor Evoked Potential Obtained by

Transcranial Magnetic Brain Stimulation in Motor Function Recovery in Patients With Acute Ischemic Stroke. Stroke.1998;29:1854-1859. doi:10.1161/01.STR.29.9.1854.

2. Stinear CM, Barber PA, Smale PR, Coxon JP, Fleming MK, Byblow WD. Functional potential in chronic stroke patientsdepends on corticospinal tract integrity. Brain. 2007;130(Pt 1):170-180. doi:10.1093/brain/awl333.

3. Bradnam L V, Stinear CM, Barber PA, Byblow WD. Contralesional hemisphere control of the proximal paretic upper limbfollowing stroke. Cereb Cortex. 2012;22(11):2662-2671. doi:10.1093/cercor/bhr344.

Funding: This project was supported by funds from the University of Minnesota’s Program in Physical Therapy.

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The effects of anodal tDCS over the supplementary motor area on gait initiation in people with Parkinson’s disease with freezing of gait

Sommer L. Amundsen Huffmaster1,2, Chiahao Lu1,2, Paul J. Tuite2, Colum D. MacKinnon1,2

1. Movement Disorders Lab, University of Minnesota. 2. Department of Neurology, University of Minnesota

Background: Supplementary motor area (SMA) activity is reduced in people with Parkinson’s disease (PD), contributing to impaired self-initiated movements1. People with PD who have start hesitation and freezing of gait (FOG) initiate gait with reduced or absent anticipatory postural adjustments (APAs) that are required for balance and forward propulsion2. Anodal transcranial direct current stimulation (tDCS) increases the excitability of cortical structures beneath the stimulation site3. We investigated if anodal tDCS over the SMA can transiently improve APA magnitudes compared to sham (no current) in people with PD and FOG.

Methods: In this double-blinded, cross-over study, 8 PD patients (3 females) with FOG (68 ± 9 years, off medication) underwent 2 sessions of gait initiation testing (sham or anodal tDCS at 1 mA for 10 min, separated by >1 week). Structural 3-T MRI scans and Brainsight software were used to target stimulation to the scalp surface over the SMA. Eight gait initiation blocks (5-6 trials/block) were collected: (1) pre-tDCS, externally cued; (2) baseline pre-tDCS, self-initiated; and (3-8) post-tDCS at 12 min intervals, self-initiated. For self-initiated trials, subjects stood for 3-5 seconds before walking forward. For cued trials, subjects were given acoustic “warning” and “go” tones. Forceswere collected at 1000 Hz for 8 sec from force plates beneath the feet. APA magnitudes were quantified using Matlab(Mathworks, MA). A two-way repeated measures ANOVA (factors: stimulation type and time) was performed.Outcome measures included step foot peak loading force, stance foot peak unloading, peak lateral shift of the centerof pressure (COP) towards the step foot, and peak anterior COP shift.

Results: External cues increased all APA magnitudes relative to baseline self-initiated trials (p<0.001). No significant changes in APA magnitudes were found following anodal or sham tDCS compared to baseline (p>0.355) (figure 1). For 2 subjects, anodal tDCS significantly worsened performance (p<0.001-0.017), 2 subjects improved performance (p=0.001-0.043), and 4 subjects showed no changes. There was no effect of visit order (p=0.246-0.883).

Conclusions: The results suggest that tDCS applied over the SMA does not consistently improve, or may worsen, gait initiation in people with PD with FOG. The lack of significance may be related to dosing and location of tDCS or could suggest that the SMA does not contribute to gait initiation impairment in people with FOG. Future studies should differentiate potential “responders” or “non-responders” to anodal tDCS over the SMA. References:

1. Sabatini U, Boulanouar K, Fabre N, Martin F, Carel C. Cortical motor reorganization in akinetic patients with Parkinson'sdisease. Brain. 123: 394-403, 2000.

2. Rogers MW, Kennedy R, Palmer S, Pawar M, Reising M, Martinez KM, Simuni T, Zhang Y, MacKinnon CD. Posturalpreparation prior to stepping in patients with Parkinson's disease. J Neurophysiol. 106: 915-924, 2011.

3. Stagg CJ, O’Shea J, Kincses ZT, Woolrich M, Matthews PM, Johansen-Berg H. Modulation of movement-associatedcortical activation by transcranial direct current stimulation. European Journal of Neuroscience 30: 1412–1423, 2009.

Funding: NIH NINDS R01 NS070265, MnDRIVE Postdoctoral Fellowship, NIH NCATS UL1TR000114.

Figure 1. Results for sham (squares) and anodal-tDCS (circle) on 1 sample APA measure (peak loading vertical force of the step foot) over the 8 blocks of trials. The cued block of trials was significantly different (p<0.001) than the self-initiated blocks of trials for all measures and both stimulation conditions.

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Title: Astrocytes Stimulation of Magneto-electric Nanoparticles outside Brain Blood Barrier

Authors: Kun Yue, and Alice C. Parker

Affiliations: Ming Hsieh Department of Electrical Engineering, University of Southern California, USA.

Background: Recent research has demonstrated that astrocytes may be active player in the DBS mechanism of action including astrocyte signaling, glutamate regulation, ATP regulation, etc. To verify the possible mechanisms of astrocytes under HFS and develop advanced DBS system, we proposal large-scale astrocytes stimulation with magneto-electric nanoparticles (MNPs). MNPs can be precisely controlled by external magnetic field, which will enable much more complicated input patterns than DBS. Furthermore, the particles aim to the astrocytes in the Brain Blood Barrier through injection, so it is minimal-invasive surgery operation and can be expelled after certain time period. We implemented mathematical simulations to check the possibility of this stimulation method.

Methods The simulation of voltage dependent calcium channels derived from Reuter-Stevens (RS) and the Goldman-Hodgkin-Katz (GHK) models, the total charge in calcium imported into the cell during the period of electric stimulation was derived from the current-voltage relationship. The simulation of calcium oscillation in astrocytes derived from Hodgkin-Huxley (HH) equation and the Lavrentovich and Hemkin's (LH) model. The simulation of NMDA receptor derived from Izhikevich model. We use DBS-Parkinson’s model to present the neuromodulation of astrocytes stimulation, the basal ganglia-thalamic network model of Parkinson’s Disease is developed from Rubin and Terman (RT) model.

Results The astrocytes can be triggered by MNPs through the voltage dependent calcium channels, and the charge moved into astrocytes can be numerical estimated in our simulation. The calcium oscillation can probably occur during stimulation and spread in the astrocytes networks, so that release glutamate to stimulate NMDA receptors. The charge released from AMPA/NMDA receptors is also numerical estimated, and input to Parkinson’s model as current. The Parkinson’s model simulation results support the astrocytes stimulation as neuromodulation method.

Conclusions We proposed a new neuromodulation method stimulating on astrocytes instead of neurons. One possible action flow diagram of astrocytes stimulation is presented in figure 1. This method characterized by large-scalability, complex input patterns, minimal-invasion, and safety could contribute to sophisticated brain signals research and neurological disorders treatment.

Figure 1. Astrocytes stimulation flow diagram.

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Reducing impulsivity and risk-taking behavior using transcranial direct current stimulation Casey S. Gilmore1,2, Molly R. Carson1,2, Carolyn L. Gentz1,2, Patricia J. Dickmann2,3, Greg J. Lamberty2,3,

Michael T. Armstrong2, Kelvin O. Lim1,2,3

1. Defense and Veterans Brain Injury Center, Minneapolis, MN; 2. Minneapolis VA Health Care System,Minneapolis, MN; 3. Dept. of Psychiatry, University of Minnesota, Minneapolis, MN

Background: Impulsivity is a multidimensional construct that includes a lack of premeditation, sensation-seeking, and impaired cognitive control. Impulsivity is observed in a variety of psychiatric disorders, and manifests as aggression, poor decision-making, and excessive risk-taking. Previous studies involving healthy subjects have applied transcranial direct current stimulation (tDCS) over dorsolateral prefrontal cortex (DLPFC) - an area involved with cognitive control functions - inducing a significant decrease on performance measures of risk-taking (e.g. Balloon Analog Risk Task (BART); Risk Task). The purpose of this study is to explore the effects of tDCS on risk-taking across a broad range of subjects who exhibit clinically-relevant impulsivity.

Methods: Subjects complete two tDCS sessions per day for five days with additional one and two month follow-up sessions. Subjects complete questionnaires of impulsivity (e.g. Barratt Impulsiveness Scale; BIS), and pre- and post-intervention behavioral measures of risk-taking (e.g. Delay Discounting Task, Risk Task). Subjects are randomly assigned to receive either active or sham tDCS during performance of the BART at each of the ten sessions. At the follow-up sessions, subjects complete the questionnaires and risk-taking tasks.

Results: Preliminary results on six subjects, three receiving active tDCS and three receiving sham tDCS, suggest that active tDCS (compared to sham) can effectively reduce 1) risk-taking propensity as measured by performance on the BART, and 2) impulsivity as measured by change in BIS scores from baseline to post-treatment. Averaged across BART sessions, the active tDCS group had a significantly lower adjusted number of balloon pumps (an indication of less risky behavior) than did the sham stimulation group. Subjects’ impulsiveness, as measured by total score on the BIS, decreased an average of 16% in the active tDCS group while only decreasing 4% in the sham group when comparing the first and last days of tDCS treatment.

Conclusions: This study provides preliminary evidence that tDCS may effectively reduce impulsive and risk-taking behavior in subjects who exhibit clinically-relevant impulsivity, extending previous research that has only included healthy subjects. This study aims to measure the magnitude of change on a number of outcome tasks from pre- to post-intervention, and the stability of these effects over time. Further, this study could have potential application as a non-invasive clinical intervention for treating patients with decreased cognitive control.

Funding: This study is supported by the Defense and Veterans Brain Injury Center.

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Inter-Individual Differences in the Induced Electric Field from Transcranial Magnetic Stimulation

E. G. Lee1, R. L. Hadimani1, 2, D. C. Jiles1

1. Iowa State University, USA; 2. Virginia Commonwealth University, USA

Background: Transcranial magnetic stimulation (TMS) is a promising tool for non-invasive neuromodulation that utilizes a time-varying magnetic field to induce an electric field (E-Field) in the brain [1]. There is inter-individual variability in anatomical features relevant to TMS that contribute to the intensity and focality of the induced E-Field from TMS [2]. Variability in the induced E-Field can explain why some people respond to repetitive TMS (rTMS) differently than others. Computer simulations to model the induced E-Field from TMS are common but most simulation studies use a single model, leaving them unqualified to quantify the inter-individual differences in the induced E-Field from TMS. To investigate inter-individual features of the induced E-Field, we calculate several E-Field related parameters for fifty heterogeneous head models. These include the maximum E-Field intensity in the brain (E-Max), the volume of the brain with an E-Field value of at least half E-Max (V-Half), and the location of E-Max. These calculated parameters were also compared to brain-scalp distance (BSD) and assessed using different coil orientations.

Methods: Fifty head models representative of Human Connectome Project participants’ MRI images were developed using the automated SimNIBS pipeline [3]. Each model was constructed from T1 and T2 weighted MRI images with 0.7 mm resolution. The induced electric field in all tissues was calculated using finite element simulations in SEMCAD X with a Magstim 70 mm Figure Eight coil used for stimulation on the vertex. Different parameters described in the background section were calculated using custom Matlab scripts.

Results: Simulation results showed significant inter-individual variation in all calculated parameters of the induced E-Field. As expected, BSD was a good predictor of E-Max (correlation coefficient = -.764). Significant variation wasobserved in V-Half, with no significant relationship to BSD. The location of E-Max was on average over 1 cm fromthe projected location of E-Max and commonly changed depending on coil orientation. Further it was observed thatcoil orientation could also be used to increase or decrease both E-Max and V-Half.

Conclusions: Results show that there is significant inter-individual variability in the induced E-Field from TMS in E-Max, V-Half, and in the location of E-Max. The E-Field from TMS is the driving factor for neuronal stimulation, and factors such as these should be explored further to better understand how they relate to clinical outcomes for the use of rTMS in depression and with other neurological disorders. References: [1] V. Walsh and A. Pascual-Leone, "The Nuts and Bolts of TMS," in Transcranial magnetic stimulation: a neurochromometrics of mind.Cambridge, MA: MIT Press, 2003.

[2] E. G. Lee, W. Duffy, R. Hadimani, M. Waris, W. Siddiqui, F. Islam, M. Rajamani, R. Nathan, and D. Jiles, “Investigational Effect ofBrain-Scalp Distance on the Efficacy of Transcranial Magnetic Stimulation Treatment in Depression,” IEEE Trans. Magn., vol. 9464, no.c, pp. 1–1, 2016.

[3] M. Windhoff, A. Opitz, and A. Thielscher, “Electric field calculations in brain stimulation based on finite elements: An optimizedprocessing pipeline for the generation and usage of accurate individual head models,” Hum. Brain Mapp., vol. 34, no. 4, pp. 923–935,2013

Funding: This work was sponsored by the Carver Charitable Trust and the Palmer Endowment Fund.

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Title: Safe Direct Current Stimulation for the Treatment of Chronic Peripheral Pain Authors: Fei Yang1, Yun Guan1, Gene Fridman2,3

Affiliations: 1. Anesthesiology Dept., Johns Hopkins University, Baltimore, USA; 2. Biomedical Engineering Dept., Johns Hopkins University, Baltimore, USA; 3. Otolaryngology Dept., Johns Hopkins University, Baltimore, USA

Background: Electrical neuromodulation is an important strategy for treating chronic pain conditions that are refractory to pharmacotherapies. However, currently available neurostimulation pain therapies such as spinal cord stimulation (SCS) are associated with limited efficacy and side effects. We are developing a Safe Direct Current Stimulator (SDCS)1,2 that can modulate neuronal activity by using ionic direct current (iDC) for the first time. Unlike the conventional neural stimulation systems that communicate with the nervous system with biphasic pulses to avoid tissue damage at the metal tissue interface3, SDCS converts pulses delivered to the metal electrodes inside the implantable device to deliver iDC at its output to excite, suppress, or sensitize neural tissue with extracellular potential.

Methods: In an anesthetized rat model (Panel A, right), we exposed the sciatic nerve in the leg and also the spinal cord at the L4, L5 dorsal root entry region. We delivered 5mA, 2ms test electric shock (“Pain Stim”) to the distal end of the sciatic nerve intended to depolarize all neurons in the nerve, while we recorded from a wide dynamic range (WDR) neuron that receives input from both the non-noxious A and the pain-carrying C/delta peripheral fibers. This setup allowed us to detect which fibers would be blocked by application of iDCthrough a salt-bridge micro-catheter to the middle portion of the sciatic nerve to simulate the SDCS stimulation delivery method. Which types of neurons are blocked by the application of iDC could be observed by the time-of-arrival of action potentials after the shock presentation. The sensory information, carried by the fast large caliber A-fibers would arrive within 75ms after theshock presentation, while the pain signalscarried by the slow delta and C-fibers wouldarrive between 100ms and 400ms after theshock presentation.

Results: Panel B shows the example recording from a WDR neuron as cathodic iDC was applied to the block neural transmission. Panel C shows a cumulative response from 8 experiments with increased cathodic iDC intensity. Surprisingly and consistently the pain component of the transmission was preferentially suppressed by iDC delivery.

Conclusions: Our studies provide promising evidence that iDC applied at peripheral nerves could induce an effective and reversible inhibition of neural activity in pain pathways. Intriguingly, iDC (and by extension an implantable SDCS) may be optimized to preferentially inhibit “pain” signals, while allowing the other nerve signals to pass, thus avoiding potential paresthesia – an unavoidable side-effect of SCS.References:

1 G. Y. Fridman and C. C. Della Santina, "Safe direct current stimulation to expand capabilities of neural prostheses," IEEE Trans. Neural Syst. Rehabil. Eng 21(2), 319 (2013).

2 G. Y. Fridman and C. C. Della Santina, "Safe direct current stimulator 2: concept and design," Conf Proc IEEE Eng Med Biol Soc.2013;2013:3126-9.doi: 10.1109/EMBC.2013.6610203. (2013).

3 D. R. Merrill, M. Bikson, and J. G. R. Jefferys, "Electrical stimulation of excitable tissue: design of efficacious andsafe protocols," 141(2) (2005).

Funding: Johns Hopkins University Blaustein Pain Foundation, NIH R21NS081425-01A1.

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Title: Developing a Microfluidic Device for Safe DC StimulationAuthors: Annie Mao1, Patrick Ou1, Kevin King1,2, Gene Fridman1

Affiliations: 1. Johns Hopkins University, USA; 2. University of Pittsburgh, USA

Background:

We are developing a Safe Direct Current Stimulator (SDCS) device, which applies ionic direct current (iDC) to inhibit, excite, or modulate the sensitivity of neural tissue by controlling the extracellular potential. This device enables a new class of chronically implanted neural prostheses that can overcome traditional challenges of charge injection limit and electrochemical reactions at the electrode-tissue interface. The SDCS, shown in two states in Panel A, delivers AC pulses to electrodes suspended at the opposite ends of a torus filled with ionic solution. Two extension tubes connected to the sides of the torus are directed into the tissue to complete the circuit. With each change in stimulation polarity, the valves on either side of each electrode change from open-to-closed and closed-to-open, switching the direction of current flow through the microfluidic channels so that the output direction across the tissue is constant. This design is the basis for our microfluidic system, which we have demonstrated previously as a technological proof of concept1,2 and develop here as a miniaturized prototype.

Methods:

We focused on three requirements for a chronic neural prosthesis: implantable size, longevity, and safety. To achieve miniaturization, we used replica molding with a polydimethylsiloxane (PDMS) substrate and a 3D-printed master in order to fabricate saline-filled microfluidic channels and valves. Building on the work of Vyawahare et al, we designed nitinol actuators which loop over the valves3, overcoming fundamental restrictions on the stress and strain of the nitinol wire by modifying the durometer of the PDMS and designing valve architectures that minimize the force needed for closure to ensure long-term performance. A PIC microcontroller controls these valves by selectively allowing current through the nitinol wires, inducing contraction and pinching the valve shut (Panel B). In order to avoid unsafe electrochemical reactions, we fabricated our electrodes from 7 cm of coiled PtIr wire to ensure that the electrode-saline interfaces remained below the charge injection limit.

Results:

Panel C shows the prototype of our device, which measures 30 x 30 x 30 mm. We tested a single valve operation for >500,000 cycles. The device consumes 0.255 W plus 0.073 W per closed valve.

Conclusions:

Our work suggests that it is possible to implement SDCS on a small implantable scale. Further improvements in valve performance and size reduction will continue to enhance the potential of the SDCS for chronic neural prosthesis applications.References:

1. G. Y. Fridman and C. C. Della Santina, "Safe direct current stimulation to expand capabilities of neural prostheses," IEEETrans. Neural Syst. Rehabil. Eng 21(2), 319 (2013).

2. G. Y. Fridman and C. C. Della Santina, "Safe direct current stimulator 2: concept and design," Conf Proc IEEE Eng Med BiolSoc.2013;2013:3126-9.doi: 10.1109/EMBC.2013.6610203. (2013).

3. Vyawahare S, Sitaula S, Martin S, Adalian D, Scherer A. Electronic control of elastomeric microfluidic circuits with shapememory actuators. Lab Chip. 2008 Sep;8(9):1530-5. doi: 10.1039/b804515a. Epub 2008 Jul 9. PubMed PMID: 18818809.

Funding: NIH 1R21NS081425-01A1, MED-EL Corporate Grant

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Title: Bilateral cortical silent period evoked by transcranial magnetic stimulation in a child with perinatal stroke: understanding cortical inhibitory circuits

Authors: Maíra C. Lixandrão, PhD student, PT1,2; Tonya Rich, PhD student, MA, OTR/L2; Chao-Ying Chen, PhD, PT2; Bernadette Gillick, PhD, MSPT, PT2

Affiliations: Federal University of Sao Carlos, Brazil; 2. University of Minnesota, United States.

Background: Transcranial magnetic stimulation (TMS) is used to test cortical inhibitory and facilitatory circuits. The cortical silent period (CSP) is a transient suppression of a motor activity after TMS, purported to involve inhibitory gamma-aminobutyric acid-B receptors1. However, there are no published reports regarding CSP duration inchildren with stroke. The aim of this study is to report the CSP duration of the lesioned and non-lesioned brain hemispheres in a child with perinatal stroke.

Methods: A 12 year-old female child, diagnosed with perinatal arterial ischemic stroke, participated in this study. For TMS assessment, the participant was positioned in a reclined chair. Surface Ag-AgCl bipolar electrodes were placed over the right and left hand first dorsal interosseous (FDI) muscles. A 70-mm figure-of-eight coil connected to a Magstim 200 stimulator was positioned 45º posterolaterally over the approximate location of primary motor cortex. The resting motor threshold (RMT) was determined, defined as the minimum machine intensity required to elicit motor evoked potential (MEP) peak-to-peak amplitude of ≥50µV, in at least 3 of 5 trials with the target muscle at rest. For CSP assessment, TMS single-pulses at 120% RMT was delivered to the each hemisphere separately during a slight contraction of FDI muscle (20% of maximal voluntary contraction).

Results: The participant presented with right hemiparesis and reduced grip strength in the more-affected hand (57.6lbs±4.18) compared to the less-affected hand (36.33lbs±3.39). For the CSP assessment, the maximal stimulator output (MSO) intensity was set at 65% for the lesioned (RMT = 54% MSO) and 48% for non-lesioned hemisphere (RMT = 40% MSO). After an average of 18 pulses, CSP duration results were was found to be longer for the lesioned hemisphere (170.45±10.04ms) compared to the non-lesioned hemisphere (68.15±21.58ms) (Figure 1).

Conclusions: The CSP duration of healthy adults has been reported to ranging between 150-300ms1. In adults withstroke, CSP has been found to be of longer duration in the lesioned hemisphere (237–487ms) and shorter duration in the non-lesioned hemisphere (126.5–243.5ms)2. However, a study with typically developing children reported CSPdurations between 25.5-53.8ms3. Considering that typically developing children have reportedly shorter CSPdurations than adults, and using the same criteria, we found a similar CSP duration in non-lesioned hemisphere yet a longer CSP duration in the lesioned hemisphere in this child with perinatal stroke. This longer CSP duration could be related with increased activity of inhibitory interneurons in the motor cortex after stroke2.

Figure 1. CSP of lesioned (A) and non-lesioned hemisphere (B) of a child with perinatal stroke. CSP onset (square) is defined as the final of the MEP and CSP offset (circle) is defined as the return of EMG activity that exceeds 100% of baseline standard deviation (SD) EMG activity. Triangles denote stimulus artifact. Grey line = rectified EMG. Blue line = 10ms moving SD EMG activity. Red line = 100% baseline SD EMG activity.

References: 1. Cantello R, Gianelli M, Civardi C, Mutani R. Magnetic brain stimulation: the silent period after the motor evoked potential. Neurol. 1992;42:1951-1959. 2. van Kuijk AA,Pasman JW, Geurts ACH, Hendricks HT. How salient is the silent period?The role of the silent period in the prognosisof upper extremity motor recovery after severe stroke. J Clin Neurophysiol. 2005;22(1):10-24.3. Garvey MA, Ziemann U, Becker DA, Barker CA, Bartko JJ. New graphical method to measure silent periods evoked by transcranialmagnetic stimulation. Clinical Neurophysiology. 2001;112:1451-1460.

Funding: Sao Paulo Research Foundation (Lixandrão); NIH/NICHD 5 K01-HD078484-02 (PI: Gillick), Cerebral Palsy Foundation (PI: Gillick), Foundation for Physical Therapy (PI: Gillick), UMN Marie Louise Wales Fellowship (Rich), MnDRIVE (Rich).

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The Influence of Corticospinal Tract Activation on Cortical Connectivity Evaluation: A TMS-EEG Study

Nessa Johnson1*, Sara Petrichella1,2*, Bin He1,3

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Computer Science andComputer Engineering, University Campus Bio-Medico, Italy; 3. Institute for Engineering in Medicine, University of

Minnesota, USA; *These authors contributed equally.

Background: Simultaneous TMS and scalp electroencephalography (EEG) can be used to assess cortical reactivity and connectivity by stimulating a cortical region and evaluating the spatiotemporal spread of activity. While the TMS-evoked potential (TEP) amplitude has been shown to increase with increased intensity, no study has directly evaluated the influence of peripheral muscle activity on TEPs. The aim of this study is to evaluate the TMS evoked dynamics within the motor network, and the effect of peripheral motor evoked potentials on the evoked activity and network connectivity.

Methods: Seventeen healthy subjects (age 23±11, 12F) participated. TMS pulses were applied at motor threshold to hand motor areas using a 70-mm figure-of-eight coil with a Magstim Rapid2 stimulator, while 64 channel EEG data were acquired. A neuronavigation system was used to localize the stimulation targets. The EMG response was continuously monitored for all subjects, and recorded for 11 subjects, bilaterally from the first dorsal interosseous. Each subject underwent two TMS blocks of 100 trials at 0.2 Hz, one to left M1 one to right M1. The EEG data were inspected for extreme values, low pass filtered, downsampled, baseline corrected, averaged, and sorted into MEP and no-MEP groups using EMG responses. Source imaging and connectivity analysis were performed using the eConnectome MATLAB toolbox (He et al., 2011).

Results: Single pulse TMS of left and right M1 evoked EEG activity lasting up to 300 ms composed of a sequence of deflections with positive peaks in channel Cz at 30ms, 60ms, and 170ms post-TMS and negative peaks at 46ms, 100ms, and 278ms post-TMS. Cortical excitability results significantly (p<0.05) differed between the MEP and no-MEP conditions for left M1 TMS at 60 ms (electrodes CP1,CP3,C1) and for right M1 TMS at 54 ms (electrodes CP6,C6). For both stimulation conditions, the difference in amplitude (µV) is not only present in the motor hand area but also in the centro-posterior areas, with increased amplitudes in the MEP condition compared to the no-MEP condition. Connectivity analysis revealed higher outflow and inflow from M1 to somatosensory cortex for trials with MEPs than those without for both left M1 TMS (60,100,164 ms) and right M1 TMS (54,100,164 ms).

Conclusions: Corticospinal activation along with the resulting somatosensory feedback, directly affects the cortical activity and dynamics within motor areas. The findings suggest that TMS-EEG, along with adaptive connectivity estimators, can be used to evaluate the cortical dynamics associated with sensorimotor integration and proprioceptive manipulation.References: He, B., Dai, Y., Astolfi, L., Babiloni, F., Yuan, H., & Yang, L. (2011b). ‘eConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity’. Journal of Neuroscience Methods, vol. 195, no. 2, pp. 261-269.

Funding: NSF DGE-1264782, NIH EB006433

Figure 1: TMS-evoked potentials following stimulation over right primary motor cortex split between trials resulting in a hand muscle response (MEP) (left) and those without an MEP (right). (Upper) Butterfly plot of the average TMS-evoked activity from all electrodes. (Lower) Voltage distributions and cortical current density estimates of the TMS-evoked activity for each peak.

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Improving Motor Recovery after Stroke by Combined rTMS and BCI TrainingNessa Johnson1, Albert You1, James Carey2, Ann van de Winckel2, Andrew Grande3, Bin He1,4

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Physical Therapy,University of Minnesota, USA; 3. Department of Neurosurgery, University of Minnesota, USA;

4. Institute for Engineering in Medicine, University of Minnesota, USA

Background: Treatment strategies to address motor impairment after stroke should optimally address both contributors towards hemiparesis, namely by encouraging activity within the lesioned hemisphere and down regulating inhibition from the healthy hemisphere. In this study, we sought to combine repetitive Transcranial Magnetic Stimulation (rTMS) with motor imagery Brain Computer Interface (BCI) training to enhance motor recovery after stroke. The combined treatment uses rTMS to inhibit the non-stroke side (dis-inhibit the stroke side) and BCI to encourage activity in the stroke side.

Methods: Two stroke patients have completed the study (1F, age 37 and 60, both 12M post stroke at enrollment).rTMS was applied for 10 minutes at 1Hz at 90% rMT for FDI applied to motor hotspot of non-stroke side using a 70-mm figure-of-eight coil with a Magstim Rapid2 stimulator. BCI training immediately followed using a virtual reality based reach and grasp task with left and right targets, with 20 trials per run and 8 to 10 runs per session. A 64 channel BrainAmp MR EEG system and BCI2000 were used to control the stimulus presentation (with auditory cues). Nine combined rTMS/BCI sessions were completed (3X per week), followed by nine sessions of BCI training only (3X per week). Clinical tests of motor performance (Box and Block, Motricity, finger tracking), paired-pulse TMS inter-hemispheric inhibition (IHI) tests (using two 50mm figure-of-eight coils with a Magstim Bistim2 stimulator), and functional MRI (during finger tracking and rest) were evaluated at three time points: baseline, post-rTMS/BCI (3 weeks), and post-BCI (6 weeks).

Results: Both subjects were able to achieve adequate control of the virtual reality BCI paradigm, with a peak percentage of 95% of correct responses, and a daily average of nearly 70% correct responses in the final BCI sessions. Performance improvements were observed on the finger tracking test and the Box and Block Test over time, but not in the Motricity test. Importantly, IHI testing revealed a significant decrease in IHI from the non-stroke hemisphere acting upon the stroke hemisphere as a result of rTMS treatment, and functional MRI results suggest increased cortical activation during movement within the stroke hemisphere over the course of rTMS and BCI treatment.

Conclusions: The results demonstrate the feasibility of combining rTMS with BCI training in stroke patients, and lay a foundation for continued work with additional subjects to evaluate the potential of this combined therapy.Funding: NSF DGE-1264782, NIH EB006433

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Closed-loop deep brain stimulation effects on parkinsonian motor symptoms -- is beta enough? Luke A. Johnson1, Shane D. Nebeck1, Abirami Muralidharan1, Matthew D. Johnson2, Kenneth B. Baker1, Greg

Molnar1, Jerrold L. Vitek1

1. University of Minnesota, Department of Neurology, USA; 2. University of Minnesota, Department of BiomedicalEngineering, USA

Background:Recently there has been great interest in the potential to improve deep brain stimulation (DBS) approaches for the treatment of Parkinson’s disease (PD) by incorporating feedback controls based on real-time measures of brain activity (i.e. closed-loop DBS). Technological advances by device manufacturers will enable some forms of closed-loop DBS in patients in the near future, however there persists a significant gap between those technical capabilities and the understanding of what brain-based biomarkers ought to be used and how best to incorporate them into an algorithm for closed-loop DBS. A number of studies have recorded excessive beta oscillations in local field potentials (LFPs) in the subthalamic nucleus (STN) coincident with untreated PD symptoms such as rigidity and bradykinesia [1], leading to the hypothesis that STN beta LFPs may be an effective programming biomarker for real-time, closed-loop control of DBS [2]. In the present study, we implemented a closed-loop DBS (CL-DBS) strategy that delivers stimulation to the STN based on the level of beta LFPs recorded directly from a STN DBS lead implanted in a parkinsonian non-human primate.

Methods Data were collected from one female rhesus macaque rendered parkinsonian with the neurotoxin 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP) and implanted in the STN with a 4-contact scaled version of a human DBS lead (NuMed). Therapeutic effects of CL-DBS and traditional continuous DBS (tDBS) relative to the Off-DBS condition were evaluated via a clinical rating scale and objective performance in a cued reaching task.

Results CL-DBS was comparable to tDBS at reducing rigidity, while reducing the amount of time DBS was on by ≈50%; however, only tDBS improved bradykinesia during the reaching behavior. Beta activity was dynamically modulated during movement, and our findings suggest that poor performance during the reaching task was due to reach-related reductions in beta amplitude that influenced the timing and duration of stimulation in the CL-DBS condition.

Conclusions These results illustrate the promising utility of closed-loop DBS devices for PD based on STN beta LFP levels; however the real-time sensing of a single LFP frequency alone may not be robust enough. Thus, the data also suggest the potential need of additional features and using multiple objective measures when evaluating its full therapeutic potential.

References:

[1] A. A. Kuhn, A. Tsui, T. Aziz, N. Ray, C. Brucke, A. Kupsch, et al., "Pathological synchronisation in the subthalamic nucleus ofpatients with Parkinson's disease relates to both bradykinesia and rigidity," Exp Neurol, vol. 215, pp. 380-7, Feb 2009.

[2] S. Little, A. Pogosyan, S. Neal, B. Zavala, L. Zrinzo, M. Hariz, et al., "Adaptive deep brain stimulation in advanced Parkinsondisease," Annals of Neurology, vol. 74, pp. 449-457, 2013 2013.

Funding: This study was funded in part by the National Institutes of Health, National Institute of Neurological Disorders and Stroke (NS-037019). Postdoctoral fellowship for Basic Scientists from the Parkinson’s Disease Foundation to A.M. MnDRIVE (Minnesota Discovery, Research and InnoVation Economy) Initiative Neuromodulation Post-doctoral Fellowship to L.A.J.

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Title: Phase-amplitude coupling in the STN and its change following therapeutic STN DBS in the MPTP monkey model of Parkinson’s disease

Authors: Jing Wang1, Shane Nebeck1, Luke A. Johnson1, Jianyu Zhang1, Matthew D. Johnson2,Kenneth B. Baker1, Jerrold L. Vitek1

Affiliations:1. Department of Neurology, University of Minnesota, US2. Department of Biomedical Engineering, University of Minnesota, USBackgroundAlthough beta oscillations have been considered a biomarker of the parkinsonian state, more recent studiessuggest alterations in phase-amplitude coupling (PAC) in the pallidothalamo-cortical circuit may also play a role in the development of the motor signs associated with Parkinson’s disease (PD). PAC has been observed in the primary motor cortex and subthalamic nucleus (STN) in PD patients, and is reduced by therapeutic STN deep brain stimulation (DBS) [1, 2]. Due to limitations associated with such studies in PD patients whether thiscoupling is present in the normal state remains unclear. Similarly the effect of prolonged DBS on PAC has not been studied. In the current study, we investigated the role of PAC in both the normal and parkinsonian animalbefore and after prolonged STN DBS.

MethodsA NHP (female, 6kg) was implanted with an 8-contact scaled-down DBS lead (NuMed) in the STN. Bipolar local field potentials (LFPs) from DBS contact pairs (C0-C1, C1-C2, C2-C3) were used to determine thepresence and strength of PAC. LFPs were collected in the naïve and parkinsonian condition before and fourtimes following STN DBS with the animal at rest in a primate chair. Optimal stimulation contacts (C1+, C2−)and parameters (0.2mA, 130Hz, 125μs) were determined, and prolonged (4 hours) DBS was applied daily. Amotion capture system (Motion Analysis, Inc.) was used to monitor arm movements and videos of the animal’s face were taken to identify eyes-open episodes to insure the animal was awake. Eyes-open resting LFPs weredivided into 25s data blocks for power spectrum density [3] and PAC analysis [4].

ResultsCompared to the normal condition we observed an increase in beta/gamma PAC in C0-C1 and C1-C2, but not inC2-C3 in the parkinsonian state. We also observed an elevation of power in the beta frequency band and a reduction in gamma band across C0-C1 and C1-C2. Beta/gamma coupling was reduced in C1-C2 after 4 hoursof DBS and gradually returned to pre-DBS levels marked by the same trend of change in both mean and maximum modulation indexes of PAC (Wilcoxon test, p<0.05). The return of PD motor signs paralleled the return of PAC. However, this change was not observed in the beta or gamma power, and only weak correlation was found between beta power and beta/gamma PAC (correlation coefficient=0.37).

ConclusionsThe increased beta/gamma PAC in the STN in PD and its reduction after prolonged DBS supports thehypothesis that PAC may serve as a pathophysiological biomarker for the altered movement observed in PDand possibly for other basal ganglia disorders [5].

References[1] Yang, A. I., et al. Beta-coupled high-frequency activity and beta-locked neuronal spiking in the subthalamic

nucleus of Parkinson's disease. The Journal of Neuroscience (2014).[2] de hemptinne, C., et al. Therapeutic deep brain stimulation reduces cortical phase-amplitude coupling in

Parkinson's disease. Nature neuroscience (2015).[3] Bokil, H., et al. Chronux: A platform for analyzing neural signals. Journal of Neuroscience Methods (2010).[4] Aru, J., et al. Untangling cross-frequency coupling in neuroscience. Current opinion in neurobiology (2015).[5] Wang, D.D., et al. Subthalamic local field potentials in Parkinson's disease and isolated dystonia: An

evaluation of potential biomarkers. Neurobiology of Disease (2016).FundingNIH grants NS037019, NS077657 and MnDRIVE neuromodulation post-doctoral fellowship

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Effects of Short-Term Mind-Body Awareness Training on Sensorimotor Rhythm based

Brain-Computer Interface

James R. Stieger1, Christopher C. Cline1, Andy Huynh1, Angeliki Beyko1, Stephen A. Engel2, Bin He1,3

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Department of Psychology, Universityof Minnesota, USA; 3. Institute for Engineering in Medicine, University of Minnesota, USA

Background: The merits of yoga and meditation, collectively known as mind body awareness training (MBAT), have been promoted for millennia. Nevertheless, the systematic study of changes in neural activity due to MBAT has been a relatively recent endeavor. MBAT is characterized by state changes (alterations in neural activity while practicing MBAT), as well as trait changes (differential neural activity that persists after MBAT) [1]. Previous work has demonstrated that those who practice MBAT show a greater ability to learn to control sensorimotor rhythm (SMR) based brain computer interfaces (BCI) [2]. However, a key question has yet to be answered: is this behavioral improvement due to the trait changes from MBAT, or to the fact that those that choose to undergo MBAT have a natural affinity for mental training? In this study, we use an SMR based BCI [3] and a 6-week MBAT program to address this question.

Methods: 14 MBAT naive subjects attended a 6-week Yoga Nidra class. Their BCI learning was compared with 6 initial performance-matched controls across 6 EEG-based BCI training sessions. Motor imagery of hand movement was used by subjects to modulate their EEG in the mu band, which was decoded using established methods [3] in order to control a virtual cursor. Subjects imagined right hand movement to move the cursor right, left hand movement to move the cursor left, movement in both hands to move the cursor up, and a voluntary rest to move the cursor down. Trials were separated into left/right (LR) only, up/down (UD) only, and combined 2D paradigms. Accuracy was assessed using a percent valid correct (PVC) metric.

Results: Overall, MBAT subjects outperformed the control subjects in terms of accuracy in every cursor task. The increases in accuracy were 11%, 6%, and 10% in the LR, UD, and 2D paradigms, respectively. Additionally, the MBAT group demonstrated a greater proportion of subjects reaching 1D mastery (75% compared with 60%).

Conclusions: The present results suggest that this particular MBAT intervention leads to an increased aptitude for SMR based BCI control. The improved behavioral performance implies that short-term MBAT alone may lead to an enhanced ability to modulate the mu SMR. The marginal statistical significance of the observed effect may be in part due to the small sample size; current work is expanding the sample.

References:[1] Lomas, T., et al., “A systematic review of the neurophysiology of mindfulness on EEG oscillations,” Neuroscience &

Biobehavioral Reviews, vol. 57, pp. 401–410, Oct. 2015.[2] Cassady, K., et al., “The impact of mind-body awareness training on the early learning of a brain-computer interface,”

TECHNOLOGY, vol. 02, no. 03, pp. 254–260, Sep. 2014.[3] He B., et al., “Sensorimotor Rhythms based Noninvasive Brain-Computer Interfaces,” Proceedings of the IEEE, 103(6): 907-

925, 2015.

Funding: NIH R01 EY023101, 2T32 EB008389-06A1, NSF CBET-1264782, NSF DGE-1069104.

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Sensitivity Analysis of Transcranial Magnetic Stimulation: A Computational Modeling Study Christopher C. Cline1, Nessa N. Johnson1, Bin He1,2

1. Department of Biomedical Engineering, University of Minnesota; 2. Institute for Engineering in Medicine,University of Minnesota

Background: Transcranial magnetic stimulation (TMS) is a noninvasive neuromodulation technology that uses strong transient magnetic fields to induce electrical current in the brain, modulating neural activity in the targeted region. Electric fields induced in the brain are highly dependent on subject-specific characteristics, such as individual cortical geometry and relative coil orientation. Recent work has demonstrated the feasibility of using computational modeling to predict fields induced by TMS in individual subjects [1]. However, such models involve many assumptions that can influence the predicted outputs. In this work, we explore sensitivity of these models to changes in bulk tissue properties and other parameters.

Methods: Anatomical T1-weighted MRI data from human subjects were used with SimNIBS, an automatic tissue segmentation and mesh generation software pipeline [1], to generate subject-specific head models. Electric fields induced in the brain by a typical TMS figure-8 coil positioned over primary motor cortex were predicted with an FEM solver, assuming isotropic piecewise homogeneous tissue conductivities. Models were constructed with a range of conductivities and other parameters varying from typical defaults, and the results were compared to determine model sensitivity to these parameters. An estimate of activation spread was used as a metric of stimulation focality [2].

Results: Variations in conductivity of CSF, gray matter (GM), and white matter (WM) were found to have the strongest influence on induced electric fields in the cortex. There is less uncertainty about exact conductivity values for CSF, but recent measurements indicate that in vivo values for GM and WM conductivity may differ by as much as a factor of 3 from more commonly used ex vivo values [3]. Over such ranges of variation in conductivity, we found activation spread to vary as much as 20%, along with other effects on stimulation intensity and profile.

Conclusions: Assumptions about bulk tissue parameters may strongly influence the results of computational models of TMS, and it is critical to consider these interactions when interpreting simulation results. Further work is needed to more robustly characterize in vivo values of tissue conductivity and permittivity, and examine differences in these parameters both across anatomical regions within an individual, and across individuals. Such information would facilitate the construction of more realistic computational models with greater predictive accuracy. References:

[1] M. Windhoff et al., “Electric field calculations in brainstimulation based on finite elements: an optimized processingpipeline for the generation and usage of accurate individual headmodels.,” Hum. Brain Mapp., vol. 34, pp. 923–935, 2013.

[2] Z.-D. Deng et al., “Electric field depth-focality tradeoff intranscranial magnetic stimulation: Simulation comparison of 50 coildesigns,” Brain Stimulat., vol. 6, no. 1, pp. 1–13, Jan. 2013.

[3] T. Wagner et al., “Impact of brain tissue filtering onneurostimulation fields: A modeling study,” NeuroImage, vol. 85,pp. 1048–1057, Feb. 2014.

Funding: This work was supported in part by NSF IGERT DGE-1069104 and NSF CBET-1264782.

Figure 1: Activation spread as a function of conductivity.Conductivity values are normalized relative to default values:0.465,0.010,1.654,0.276,and0.126S/mforskin,skull,CSF,GM,and WM respectively. Stimulation spread is calculated assuprathreshold volume divided by maximum suprathresholddepth, using half the maximum electric field magnitude as athreshold.

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Sensorimotor rhythm BCI with simultaneous high definition-transcranial direct current stimulation alters task performance

Bryan S. Baxter1, Bradley Edelman1, Nicholas Nesbitt1, Bin He1,2

1. Department of Biomedical Engineering, 2. Institute for Engineering in Medicine, University of Minnesota,Minneapolis, MN, USA

Background: A challenge for broad applications of sensorimotor rhythm based brain-computer interface (BCI) is the need for extensive training to acquire useful control of a cursor or physical object [1-2]. Transcranial direct current stimulation (tDCS) has been used to alter the excitability of neurons within the cerebral cortex in order to improve motor learning and performance [3]. We aim to test the hypothesis that utilizing high definition tDCS (HD-tDCS) will alter the performance of sensorimotor rhythm based BCI within a single session and across sessions over multiple days.

Methods: 29 healthy subjects naïve to BCI control were randomized into anodal, cathodal, and sham groups and participated in three experimental sessions of 1D left/right hand motor imagination performance. A 64-channel EEG system was used to record and a 4x1 HD-tDCS was used to stimulate all subjects, with the center electrode located between C3 and CP3 and return electrodes located between adjacent EEG electrodes. Subjects performed motor-imagery BCI tasks before, during, immediately after (I-Post), and 30 minutes after (D-Post) 20 minutes of 2mA tDCS stimulation.

Results: We report a decreased time-to-hit for right hand trials imagination after anodal stimulation both within and across sessions (Figure 1). Additionally, we found differing after-effects of stimulation on the electrophysiology of the stimulated sensorimotor cortex during online BCI task performance for right hand trials based on the stimulation type. Sham and anodal stimulation groups had increased online alpha power over the stimulated region for right hand trials immediately after stimulation; the cathodal stimulation group did not show this increase. These differences were not seen in left hand imagination trials nor were they seen in sensorimotor electrodes in the contralateral hemisphere for either left or right hand trials.

Figure 1. Time to hit within a session normalized to the pre-stimulation baseline. The anodal group has a reduced time-to-hit for right hand trials following stimulation. Values: Mean +/- S.E. *p<0.05.

Conclusions: Unilateral HD-tDCS alters electrophysiology and behavior during BCI performance based on task specific neural activation within and across experimental sessions. The decreased time to hit right hand targets after anodal stimulation suggests stimulation can reduce response time in a targeted manner. The decreased C3/CP3 alpha power after cathodal stimulation suggests this stimulation may impair a subject’s ability to modulate their sensorimotor rhythm power. These effects should be considered when applying noninvasive brain stimulation to improve BCI performance and other cognitive tasks.References:[1] He B, Gao S, Yuan H, Wolpaw J. Brain-computer interface. In He B (Ed): Neural Engineering, Springer, pp. 87-151, 2013.[2] He B, Baxter B, Edelman B, Cline CC, Ye WW. Noninvasive brain-computer interfaces based on sensorimotor rhythms. Proceedingsof the IEEE, 103(6): 907 – 925, 2015.[3] Reis J, Fritsch B. Modulation of motor performance and motor learning by transcranial direct current stimulation. Curr. Opin. Neurol.24(6): 590–6, 2011.

Funding: This work was supported in part by NSF CBET-1264782.

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Title: An externalised mobile system for closed-loop deep brain stimulation research in patients

Authors: Yunpeng Zhang1, Liang Li1, Alek Pogosyan2, Peter Brown2, Shouyan Wang1*

Affiliations:1 Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China 2 Medical Research Council Brain Network Dynamics Unit at University of Oxford, Oxford, OX3 9DU,UK* Email: [email protected]

BackgroundClosed-loop deep brain stimulation shows significant potential in improving the outcome of treatment inParkinson's disease, reducing power consumption and side effects[1]. There is a relative lack of research tools with which to assess and verify closed-loop neuromodulation strategies in patients [2]. This workaimed to develop an externalized, mobile, closed-loop deep brain stimulation system with real-timeprocessing and the ability to record multiple types of neurological signal.

MethodsThe neurophysiological recording module was made with an integrated chip, which provided 24-bitsampling resolution and large dynamic range for simultaneous LFP/EEG/ECG/EMG/EOG recording.The real-time computation capacity was 128MHz. The neurological signals were stored through wireless transmission, SD-card storage or optical connection to a PC computer. Two channels for electricalstimulation provided independently bilateral arbitrary waveforms that could be delivered to any contacts of a deep brain stimulation electrode with switches.

ResultsThe size of the system was 15.0x9.5x4.0cm and weight 350g. It was rechargeable and comfortable to carry for long periods. Stimulation artefacts were suppressed by hardware filtering and filtered out bydigital filtering. The system was able to deliver either bipolar or unipolar stimulation and record bipolarLFP during stimulation. Algorithms allowing filtering, FFT, and PID control were integrated in the system which was also able to communicate with the real-time hardware system Speedgoat.

ConclusionsWe have developed an externalized mobile system to facilitate closed-loop deep brain stimulationresearch in patients which allows flexible adjustment, large dynamic range signal recording, real-timecomputation and dual channel stimulation. The system should help accelerate the implementation of closed-loop deep brain stimulation strategies in clinical research.

References

1. Little S, et al. (2013) Adaptive Deep Brain Stimulation in Advanced Parkinson Disease. Annals ofNeurology 74(3):449-457.2. Beudel M & Brown P (2016) Adaptive deep brain stimulation in Parkinson's disease. Parkinsonism &Related Disorders 22:S123-S126

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Immunohistochemical evaluation of deep brain stimulation induced neural activation Authors: Benjamin A. Teplitzky1, Matthew D. Johnson1,2

Affiliations: 1. Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 2. Institute for Translational Neuroscience, University of Minnesota, Minneapolis, MN

Background: Deep brain stimulation (DBS) is an enabling technology used to treat a range of brain disorders;however, its therapeutic mechanisms remain poorly understood. Current hypotheses are primarily supported by single-cell electrophysiological recordings in preclinical animal models of DBS. While electrophysiological recordings provide cell-specific high-resolution temporal data, broad spatial cell sampling is generally impractical.Immunohistochemistry (IHC) complements electrophysiology by providing broad spatial sampling of single-cells at a single time point, but is extremely underutilized in preclinical animal model studies of DBS. Here we demonstrate cFos and EGR1 IHC following DBS in a non-human primate.

Methods: In a terminal study, a small-diameter (0.635 mm) version of a quad-electrode DBS lead was stereotactically implanted into the right anterior limb of the internal capsule (ALIC) of an anesthetized rhesus macaque. Charge-balanced monopolar current-regulated 100 µsec digital pulses were delivered at 130 Hz through an electrode in the ALIC for 1.5 hours. Transcardial perfusion with 25mM phosphate buffered saline (PBS) followed by4% paraformaldehyde in 25mM PBS (PFA) was performed 1 hour after stimulation was stopped. The brain was postfixed, cryoprotected and sectioned at 50µm in the coronal plane. IHC was performed using the avidin-biotin-peroxidase complex method on free-floating sections. Primary antibody incubations lasted 48 hours and consisted of a polyclonal anti-cFos primary antibody or a monoclonal anti-EGR1 antibody, both diluted 1:1000.

Results: Clear nuclear staining of individual cells was observed throughout the brain. Sub-regions of the superior frontal gyrus showed robust unilateral expression of EGR1 and cFos following DBS of the ALIC. Expression of EGR1 and cFos was also detected in various regions of the basal ganglia and limbic system, but with no clear hemispheric-bias in expression.

Conclusions: Immunohistochemistry is a powerful tool that can produce rich whole-brain analysis of DBS mechanisms in non-human primates. Such whole-brain analysis with cellular resolution can provide detailed information about the spread and network effects of DBS.Funding: This work was supported by the Michael J Fox Foundation, NIH R01-NS081118, NSF-IGERT Systems Neuroengineering, DGE-1069104, and the NSF-GRFP-00006595.

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Python-based Open-Source Stereotactic Neurosurgical Planning Software Package Diana Johnson1, Simeng Zhang1, Matthew D. Johnson1,2

1. Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA; 2. Institute for TranslationalNeuroscience, University of Minnesota, Minneapolis, Minnesota, USA

Background: The anatomical targets for Deep Brain Stimulation (DBS) are usually only a few millimeters across and are commonly located next to structures that elicit adverse side effects upon stimulation. Therefore, accuracy of electrode placement is crucial to the success of DBS implants [1]. To visually aid the DBS electrode placement, a software tool, Cicerone, was developed by Miocinovic et al. in 2007 [2], and is still considered the state-of-art surgery preparation tool for preclinical stereotactic DBS neurosurgical planning, recording, and visualization with dozens of groups using the software around the world.

However, with advancements of surgical tools and improved methodology, many of the original features of Cicerone are dated. Additionally, due to the structure of the original Cicerone framework, additional functionalities are extremely challenging to implement. Hence there is need to develop a new platform that uses more efficient programming techniques. The goal for this project was to redevelop Cicerone into an object-oriented programming language (Python 2.7) with new and improved functionality, and set up a framework for an open-source software package.

Methods: Using Python, Cicerone was organized into classes, which eliminated the procedural dependency of the original code as well as many of the unnecessary repetitions. Python interfaces with Visualization Tool Kit (VTK), which allows for powerful image rendering as well as a powerful user interface. In addition to a more flexible and streamline user interface, to demonstrate the improved functionality for the new open-source Cicerone framework, a volume selection tool was implemented to select regions of interests (ROI) and side effect (SE) regions to use as input for stimulus parameter selection (programming) algorithms.

Results: The open-source Cicerone is a more powerful and user-friendly tool for DBS neurosurgical planning. It is improved in the following ways: 1) more powerful interface, 2) more efficient memory management, and 3) open-source platform in Python for integrating new features including DBS programming algorithm integration or other custom code in either Python or MATLAB.

Conclusions: The redeveloped Cicerone package provides an open-source platform for preclinical studies that require stereotactic neurosurgical planning and new opportunities for integration of computational models of other neuromodulation modalities (e.g. TMS and FUS). References: [1] Bari, Ausaf A., et al. "Improving outcomes of subthalamic nucleus deep brain stimulation in Parkinson’s disease." Expert Review of

Neurotherapeutics ahead-of-print (2015): 1-10. [2] Miocinovic, Svjetlana et al. “Stereotactic Neurosurgical Planning, Recording, and Visualization for Deep Brain Stimulation in Non-

Human Primates.” Journal of neuroscience methods 162.1-2 (2007): 32–41. PMC. Web. 23 Sept. 2015.

Funding: University of Minnesota Undergraduate Research Opportunity Program.

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Title: Particle Swarm Optimization for Programming DBS ArraysAuthors: Simeng Zhang1, Edgar Peña1, YiZi Xiao1, Steve Deyo1, Matthew D. Johnson1

Affiliations: 1Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA

Background: Targeting stimulation to key axonal pathways within the brain is critical to the success of Deep Brain Stimulation (DBS) therapy. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented around the lead perimeter. However, increasing the number of independent electrodes creates a logistical challenge with identifying (or programming) the stimulation settings to use. This clinical problem has multiple solutions, requires optimization of multiple objectives, and the trial-and-error method is inefficient and time-consuming.

Solving such complex problems is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms. Particle swarm optimization (PSO) algorithms model the simple behaviors of individuals (particles), as well as their interactions with neighboring individuals. In this study, we use PSO to identify electrode configurations and stimulation settings that optimize for three objectives: maximize axonal activation in the Region of Interest (ROI), minimize axonal activation in Side Effect regions (SE), and minimize Power consumption.

Methods: We tested the PSO approach by constructing a DBS multi-compartment myelinated axon model of the thalamus, which is a common target for treating essential tremor. This thalamic model consisted of a therapeutic region (ROI) and a side effect region (SE). We estimated the extracellular voltage field along each axon using Finite Element Modeling. Axonal activation was estimated by setting a threshold for the second spatial derivative of the voltage. Finally, we ran PSO to determine optimal electrode configurations for stimulating ROI, avoiding SE stimulation, and minimizing power consumption.

Results: Evaluating PSO accuracy and consistency, (1) predictive error was within 5%, and (2) ROI and SE activation were consistent across runs to within 0.5% and 1.5%, respectively. The algorithm was able to accommodate for (3) lead displacement by 1 mm with relatively small changes in ROI activation (within 9% irrespective of shift direction) without changing SE activation. (4) Reduction in maximum per-electrode current by 50% and 80% reduced ROI activation by 6% and 15%, respectively. (5) Disabling 3 and 12 active electrodes reduced activation by 3% and 17% respectively. Additionally, (6) runtime averaged 5.4 min per run.

Conclusions: The PSO approach provides an accurate, consistent, robust, and efficient way to obtain optimal DBSA electrode configurations for targeting therapeutic regions within complex fiber tract geometries. References: [1] Contarino et al., 2014, Neurology, [2] Kennedy et al., 1995, “Particle Swarm Optimization”, [3] Eberhart et al.,1995, “A New Optimizer Using Particle Swarm Theory”

Funding: Michael J. Fox Foundation, NIH (R01-NS081118), National Science Foundation Graduate Research Program (to EP), and NSF-IGERT Program (DGE-1069104).

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Title: Seizure Induced by Deep Repetitive Transcranial Magnetic Stimulation in an Adolescent with Depression: A Case Report

Authors: Kathryn R. Cullen1, Suzanne Jasberg1, Bonnie Klimes-Dougan2, Paul Croarkin3, Kelvin O. Lim1, Brent Nelson1

Affiliations: 1. University of Minnesota, Department of Psychiatry, U.S.A.; 2. University of Minnesota, Department of Psychology, U.S.A.; 3. Mayo Clinic

Background: Research is needed to develop novel interventions for adolescents with treatment-resistant depression (TRD). Deep repetitive transcranial magnetic stimulation (rTMS) using an H1 coil is an intervention recently approved by the FDA for treatment of TRD in adults. No studies have yet applied this technology to adolescent TRD.

Methods: We recently initiated a double-blind, sham-controlled trial to test safety and efficacy of deep rTMS (BrainSway) for adolescent TRD. In our protocol, Phase 1 consists of 20 sessions over 4 weeks of active treatment or sham (1:1 randomization), followed by unblinding. Phase 2 consists of 4 weeks of active, open-labeled treatment. Based on pivotal studies in adults,1,2 the rTMS parameters include 55 trains (2s duration), 18Hz, inter-train interval (20s), 1980 pulses per session. Energy intensity is initially set at 80-100% of motor threshold (MT) as tolerated, titrating up to target 120% MT (maximum increase rate 10%/day). Clinical response is defined as ≥50% improvement in Children’s Depression Rating Scale, Revised (CDRS-R) scores.

Results: Our first adolescent participant was a 17 year-old, unmedicated, medically-healthy female who had previously failed several antidepressant medications either due to ineffectiveness or poor tolerance. She had no history of seizure or of drug or alcohol use. Brain MRI showed no structural abnormalities. Phase 1 (sham) was well-tolerated, without clinical improvement (pre and post CDRS-R raw scores were both 60.) Weekly MT measurements were stable. For Phase 2 (active), titration began at 85% of MT and increased by 5% per day. On her first day of 120% MT (8th in the series), during the 48th train, the patient’s right cheek tensed, followed by a whole-body convulsion. TMS was discontinued. The generalized, tonic-clonic seizure lasted 90 seconds and resolved spontaneously. She was evaluated in the emergency room and discharged without anti-seizure medication. One week later, raw CDRS-R score was 57. There were no further seizures reported at 3-month follow-up.

Conclusions: We report a TMS-induced generalized tonic-clonic seizure in the first participant in our adolescent TRD trial using the BrainSway deep TMS device. Incidence of seizure with TMS in adult TRD is 1/10,000.3 However, safety and efficacy in adolescents, especially with deep TMS, is not yet known. Given the success of deep TMS for adult TRD, research investigating its use in adolescents with TRD is sorely needed. However, in light of our experience, additional precautions and alternate treatment parameters for using this device in adolescents with TRD may be needed.

References: 1. Levkovitz, Yechiel, Moshe Isserles, Frank Padberg, Sarah H. Lisanby, Alexander Bystritsky, Guohua Xia, Aron Tendler, et al. 2015.

“Efficacy and Safety of Deep Transcranial Magnetic Stimulation for Major Depression: A Prospective Multicenter Randomized Controlled Trial.” World Psychiatry: Official Journal of the World Psychiatric Association 14 (1): 64–73.

2. Berlim, Marcelo T., Frederique Van den Eynde, Santiago Tovar-Perdomo, Eduardo Chachamovich, Abraham Zangen, and GustavoTurecki. 2014. “Augmenting Antidepressants with Deep Transcranial Magnetic Stimulation (DTMS) in Treatment-Resistant Major Depression.” The World Journal of Biological Psychiatry: The Official Journal of the World Federation of Societies of Biological Psychiatry 15 (7): 570–78.

3. Carpenter, Linda L., Philip G. Janicak, Scott T. Aaronson, Terrence Boyadjis, David G. Brock, Ian A. Cook, David L. Dunner, KarlLanocha, H. Brent Solvason, and Mark A. Demitrack. 2012. “Transcranial Magnetic Stimulation (TMS) for Major Depression: A Multisite, Naturalistic, Observational Study of Acute Treatment Outcomes in Clinical Practice.” Depression and Anxiety 29 (7): 587–96.

Funding: MnDrive provided the primary study funding; BrainSway provided the use of the device at no charge for study participants.

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Cortical Sensing and Wearable Closed-Loop DBS in an Essential Tremor PatientJeffrey Herron1,2, Margaret Thompson1,2, Tim Brown1,2, Andrew L. Ko1,2, Howard J. Chizeck1,2

1. University of Washington, Seattle, WA, USA; 2. NSF Engineering Research Center for Sensorimotor NeuralEngineering (CSNE), Seattle, WA, USA

Background: While deep brain stimulation (DBS) is an effective treatment method for essential tremor [1], the open-loop nature of current neuromodulation devices may waste power and unnecessarily expose patients to side-effects. Closed-loop DBS, where sensors are used as feedback to manipulate stimulation parameters, may be able to improvetherapy for these disorders by selectively stimulating only when needed [2].

Methods: To investigate closed-loop DBS technologies in Essential Tremor patients, our team has implanted an Activa PC+S in a 58 year old male with action tremor in the right limbs. We have performed preliminary closed-loop DBS experiments using wearable electromyography (EMG) and inertial-measurement unit (IMU) sensors as means of determining both when and how therapeutic stimulation should occur. The patient was asked to repeatedly perform a task that produced tremor while receiving no stim, open loop stim, and two closed-loop stimulation algorithms. The first was an IMU-sensed tremor-modulated algorithm, where tremor band-power incremented or decremented the stimulation amplitude. The second algorithm use of EMG-sensed movement to trigger stimulation whenever the limb was being intentionally moved. We have also made use of a cortical strip electrodes placed on the patient’s upper limb motor cortex to test the feasibility of sensing movement-related beta-band desynchronization to determine when the patient is moving the limb.

Results: Both closed-loop DBS systems using the wearable sensors were able to reduce the stimulation power. The inertial tremor-modulated paradigm reduced power by 84%, and the EMG-triggering system reduced power by 53%. Both systems showed an increase of tremor when compared to open-loop performance. During the IMU trial the patient experienced 36.2% more tremor than the open-loop when normalized to no-stimulation trial. The EMG-triggered system performed much better with only 8.2% additional tremor than open-loop. When performing neural sensing experiments using the Activa PC+S, overt movements are clearly distinguishable from rest due to a broad movement related beta-band desynchronization when moving the arm or hand specifically.

Conclusions: This work demonstrates the feasibility of using wearable sensors to deliver dynamic stimulation to treat Essential Tremor. The platform we have created allows for a comprehensive investigation into different control algorithms, as demonstrated by using both IMU and EMG to control stimulation in different ways. The positive results when using EMG movement-triggered algorithm and sensing movement with the cortical strip of electrodes, future work to use cortically-sensed movement to trigger stimulation appears to be a practical method to improve DBS treatment of ET. References:[1] Benabid, Alim L., et al. "Long-term suppression of tremor by chronic stimulation of the ventral intermediate thalamic nucleus." TheLancet 337.8738 (1991): 403-406.[2] Hebb, Adam O., et al. "Creating the feedback loop: closed-loop neurostimulation." Neurosurgery Clinics of North America 25.1(2014): 187-204.

Funding: This work is supported by a donation from Medtronic and by Award Number EEC-1028725 from the National Science Foundation for the Center for Sensorimotor Neural Engineering. This research was also supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation, the DoD, or Medtronic.

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An Unsupervised Algorithm for Neural Spike Sorting inspired by Superparamagnetic Clustering Authors: Brendan Hasz1 and A. David Redish2

Affiliations: 1. Graduate Program in Neuroscience, University of Minnesota Twin Cities; 2. Department of Neuroscience, University of Minnesota Twin Cities

Background: Determining the identity of each spike from an electrophysiological recording is critical for accurately decoding information being represented in the brain. This is typically done by detecting spike times, extracting features from the spike waveforms, and then clustering the spikes in feature space, where each cluster corresponds to a unique cell. Clustering manually is extremely time intensive. Simple automatic clustering techniques often do not work well for spike sorting, whereas more sophisticated techniques are extremely computationally intensive, such as fitting Gaussian mixture models [1] or Superparamagnetic clustering [2]. Here we evaluate a clustering algorithm which was inspired by Superparamagnetic clustering, but has a far lower computational complexity.

Methods: The core of our clustering algorithm depends on a mutual K-nearest neighbors graph superimposed on a minimum spanning graph [3]. Both of these are efficiently computed using a fair-split tree. The edge weights correspond to the distance between points (spikes) in feature-space. We apply an edge threshold to the graph, such that edges longer than the threshold “break”. The connected subgraphs are the clusters. However, we always prevent the shortest edge of each node from breaking. Clusters “break off” from one another as the edge threshold is progressively lowered. Binary searches for the threshold values where breaks occur allows for fast execution time. In order to evaluate the effectiveness of this clustering method, we compare it with Gaussian mixture model fits [1]. We assess the time taken for the different methods to cluster spikes from extracellular tetrode recordings performed in our lab, and evaluate cluster quality using the L-Ratio and Mahalanobis distance. Lower L-Ratios and higher Mahalanobis distances correspond to better cluster isolation.

Results: Our algorithm took 0.133s to cluster a test dataset of 3714 spikes, each with 8 features, while a Gaussian mixture model took 3.08s. Clustering quality for both algorithms was comparable; each methods’ clustering resulted in Mahalanobis distances >50 for all clusters and L-Ratios <0.005 for 4/5 clusters. For the fifth cluster, our algorithm resulted in an L-Ratio of 0.01, while the Gaussian mixture model incorrectly classified it as two separate clusters, one with LR<0.005 and the other LR=0.74.

Conclusions: Our clustering algorithm performs faster than one of the most popular alternatives in the field, without sacrificing clustering quality. This speed improvement will help to increase throughput in neural data processing pipelines, especially for recordings with many spikes and many channels.

References: [1] Kadir, Shabnam N., Goodman, Dan F. M., Harris, Kenneth D. “High-dimensional cluster analysis with the Masked EM Algorithm.”ArXiv 1309.2848 http://arxiv.org/abs/1309.2848[2] Quiroga, R. Quian, Zoltan Nadasdy, and Yoram Ben-Shaul. "Unsupervised spike detection and sorting with wavelets andsuperparamagnetic clustering."Neural computation 16.8 (2004): 1661-1687.[3] Blatt, Marcelo, Shai Wiseman, and Eytan Domany. "Data clustering using a model granular magnet." Neural Computation 9.8 (1997):1805-1842.

Funding: NSF IGERT DGE-1069104.

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Title: Predictive and Feedback Motor Signals in the Output of Cerebellar Purkinje CellsAuthors: Martha L. Streng1, Laurentiu S. Popa2, Timothy J. Ebner1,2

Affiliations: 1. Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, USA. 2. Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA.

Background: It is widely accepted that the CNS implements forward internal models (FIMs) that predict the sensory consequences of motor commands. The predictions are then compared to the actual sensory consequences, generating sensory prediction errors (SPEs) used to improve subsequent predictions. Having access to predictive and feedback information about limb movements is of great potential value to the optimization of brain machine interfaces (BMI). Extensive research suggests that the cerebellum serves as a FIM, but the mechanisms by which SPEs are encoded are unknown. Of particular interest are the signals encoded by the primary output neurons of the cerebellar cortex, Purkinje cells (PCs). Recent results from our lab have implicated PC simple spike (SS) discharge in the processing of both prediction and feedback of arm kinematic and performance error signals. To further test this hypothesis, we are investigating how disrupting sensory information pertinent to prediction and feedback modulates SS activity.

Methods: PCs were recorded from Rhesus macaques performing a visually guided, manual pseudo-random tracking task that provides continuous measures of kinematics and performance errors. Predictive and/or feedback signals in the SS discharge were determined using temporal linear regression analysis. Visual feedback was reduced by hiding the cursor while it was inside the target or delayed by introducing a lag between manipulandum movement and cursor movement.

Results: In the feedback reduction paradigm, linear encoding of errors was reduced such that SS modulation was restricted to the target edge, where visual feedback was available (Fig 1). In the feedback delay paradigm, the timing of predictive encoding was negatively shifted equal to the duration of the delay, consistent with a forward internal model that has not adapted to the delay and makes predictions with respect to the manipulandum movement rather than the delayed cursor. Intriguingly, predictive and feedback encoding of arm kinematics was unaffected in both paradigms.

Figure 1. A) SS firing plots from PC illustrating decreased feedback signaling of position error (XE and YE) inside the target space and increased firing along the target edge. Black circles indicate target

outlines. B-C) Example regression analysis of YE encoding by SS discharge. In the Hidden Cursor Condition (red traces), magnitudes of both the R2 and beta feedback peaks are markedly reduced compared to Baseline (black traces), whereas feedforward peaks are less affected. Green traces denote control regressions on trial shuffled data.

Conclusions: Our results suggest PC SS discharge contains a rich representation of both the prediction and feedback of arm kinematics and performance errors. The differential effects of the visual feedback manipulations on error and kinematic encoding suggest the implementation of multiple FIMs. In this view, the cerebellum processes predictions and feedback about both the kinematics of arm movements and the more task-relevant performance errors to achieve optimal performance. The availability of these multiple streams of information in the discharge of PCs suggests that the cerebellar cortex may be an ideal novel target for BMI and/or neural prosthetics.

References: Shadmehr, R., Smith, M. A., & Krakauer, J. W. (2010). Error correction, sensory prediction, and adaptation in motor

control. Annu. Rev. Neurosci., 33, 89-108. Popa, L. S., Hewitt, A. L., & Ebner, T. J. (2012). Predictive and feedback performance errors are signaled in the

simple spike discharge of individual Purkinje cells. J. Neurosci., 32, 15345-15358.

Funding: Supported in part by NIH grants R01 NS18338, T32 GM008471, and F31-NS095408-01 and NSF grant IGERT DGE- 1069104.

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Title: EEG-fNIRS based assessment of neurovascular coupling during anodal transcranial direct current stimulation - parameter estimation with an autoregressive model in stroke

Authors: Anirban Dutta1, Mitsuhiro Hayashibe3, David Guiraud3, Michael A. Nitsche1,2

Affiliations: 1. Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund, Germany; 2. Department of Neurology, University Medical Hospital Bergmannsheil, Germany; 3. INRIA and

Université de Montpellier, Montpellier, France Background: Transcranial direct current stimulation (tDCS) has been shown to modulate cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity directly; while hemodynamic methods (functional near-infrared spectroscopy-fNIRS) measure this indirectly through neurovascular coupling [1]. Here, online tracking of the relation between EEG and fNIRS data acquired simultaneously from the human cortex during tDCS could provide a sensitive means to monitor the tDCS neuromodulatory effect. Methods: In this paper, we present a Kalman Filter based online parameter estimation of an autoregressive (ARX) model to track the relation between anodal tDCS induced cortical neural activity leading to changes in the EEG power spectrum (0.5-11.25Hz frequency band) and oxy-hemoglobin fNIRS signals in 5 healthy and 5 stroke subjects. Results: Our online parameter estimation technique was shown in 5 healthy subjects to be sensitive towards transient changes in the cross-correlation between EEG band-power and oxy-hemoglobin fNIRS signals in the low frequency (<0.1Hz) regime (manuscript under review [4]). In this study, we further show that these changes reflected in the alterations of ARX poles and zeros with different dead time are relevant post-stroke to monitor the tDCS neuromodulatory effect. Conclusions: This new online fNIRS-EEG tracking method may allow quantitative assessment of the existence of a coupling relationship between electrophysiological and hemodynamic response to tDCS, which could be used to monitor tDCSs’ neuromodulatory effect in health and disease. Indeed, neurovascular coupling status may be dysfunctional in acute ischemic stroke [2] which may be relevant for tDCSs’ neuromodulatory effect [3]. Therefore, EEG-fNIRS joint imaging can lend to safe dosing of tDCS in case of neurovascular coupling dysfunction.References: [1] A. Dutta, A. Jacob, S. R. Chowdhury, A. Das, and M. A. Nitsche, , vol. 39, no. 4, p. 205,

Apr. 2015.

[2] U. Jindal, M. Sood, A. Dutta, and S. R. Chowdhury, , vol. 3, pp. 1–12,2015.

[3] U. Jindal, M. Sood, S. R. Chowdhury, A. Das, D. Kondziella, and A. Dutta, “Corticospinalexcitability changes to anodal tDCS elucidated with NIRS-EEG joint-imaging: An ischemic strokestudy,” ,vol. 2015, pp. 3399–3402, Aug. 2015.

[4] M. Sood, P. Besson, M. Muthalib, U. Jindal, S. Perrey, A. Dutta, M. Hayashibe, "Online tracking ofNIRS-EEG during transcranial direct current stimulation: parameter estimation with an autoregressivemodel," under review.

Franco-Indian INRIA-DST and Franco-German PHC PROCOPE funding

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:

: Anirban Dutta1, Águida Foerster1, Michael A. Nitsche1,2

1. Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund, Germany; 2. Department of Neurology, University Medical Hospital Bergmannsheil, Germany

: This study sought to investigate two-electrode montages for anodal transcranial direct current stimulation (tDCS) over cerebellar hemisphere during visuomotor learning of myoelectric visual pursuit task (VMT) using electromyogram (EMG) from tibialis anterior (TA) muscle [1]. The cerebellar tDCS montages were selected based on computational modeling to target electric field strength at the anterior lobe (AL) or posterior lobe (PL) or AL+PL of the cerebellum [2]. The aim was to investigate, in healthy volunteers, the effect of cerebellar tDCS (c-tDCS) on lower limb VMT learning, and explore associated physiological alterations via electroencephalography (EEG).

Two-electrode montages were selected from prior works using a software pipeline that was partly based on SimNIBS. Here, we used the Intensity Contour tool of the FreeSurfer to extract the cerebellum. We conducted a randomized, single blind and sham-controlled study. Forty five (25.65 ± 7.68, 22 female) volunteers were included, and received c-tDCS, c-tDCS and lower limb motor cortex tDCS (c+M1-tDCS), or sham tDCS with our own montage. The subjects received 0.0625mA/cm2 anodal tDCS for 15 minutes during performance of VMT with the right leg. Motor learning was monitored for time and accuracy based on EMG recordings. Brain state alterations were determined via EEG.

Grimaldi and Manto montage [3] was found to be suitable for AL, Pope and Miall montage [4] for PL, and Galea et al. montage [5] for AL+PL c-tDCS from computational modeling. Time required to perform the task was significantly decreased (paired t-test, p= 0.011), compared to baseline, immediately and 24h after c-tDCS(p= 0.018). All groups showed significant increase in Alpha band power over parietal areas 1h after tDCS. Additionally, immediately after c-tDCS, a significant enhancement in Gamma band global power was observed over parietal regions.

c-tDCS affected lower limb motor learning with regard to performance speed and altered brain states of the parietal brain regions. Detailed computational modeling and neurophysiological studies are needed to clarify the mechanisms of action of different c-tDCS montages.

1. Dutta, A., Paulus, W. & Nitsche, M. A. J. Neuroengineering Rehabil. 11, 13 (2014).2. Dutta, A, SfN 2015, At Chicago, Volume: Nanosymposium - Cerebellum: Learning and Cognition

(2015).3. Grimaldi, G. & Manto, M. Ann. Biomed. Eng. 41, 2437-2447 (2013).4. Pope, P. A. & Miall, R. C. Brain Stimulat. 5, 84-94 (2012).5. Galea, J. M., Jayaram, G., Ajagbe, L. & Celnik, P. J. Neurosci. 29, 9115-9122 (2009).Franco-German PHC PROCOPE and DAAD funding

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Resting State Source Imaging Analysis of Sickle Cell Disease Patients using EEGSina Shirinpour1, Michelle Case1, Yvonne Datta1, Stephen Nelson2, Kalpna Gupta1, Bin He1

1. University of Minnesota, USA; 2. Children’s Hospitals and Clinics of Minnesota, USA

Background: Sickle cell disease (SCD) is the most commonly inherited blood disorder in the United States. SCD causes many complications, including chronic pain. Opioid analgesics are used to treat chronic pain in patients with SCD; however, due to the risks associated with opioids, patients often receive unsatisfactory pain relief because they are undertreated. Our goal is to develop an objective pain quantification method to improve pain treatment methods for patients with SCD. In order to develop this unbiased quantification method, we aim to find biomarkers of chronic pain by comparing altered neural activity of SCD patients and healthy controls using non-invasive imaging methods during resting state.

Methods: Electroencephalography (EEG) recordings were obtained from 5 healthy controls and 5 SCD patients during resting state. A 64-channel EEG cap was used for recording resting state data. All electrode impedances were kept below 20 kΩ. EEG data was recorded over 10 minute long sessions with subjects sitting in a chair in a private room with their eyes open. The EEG data was preprocessed using independent component analysis to remove artifacts. Source imaging was performed on an averaged 2 second epoch, where only artifact free segments were used to find the average. The averaged segment was filtered into different frequency bands and the inverse solution was found using the sLORETA algorithm. A realistic head boundary element model with three layers was used to localize the resting state sources1.

Results: The alpha band showed that the source localization results for healthy controls were found in the prefrontal cortex. The prefrontal cortex is one of the major nodes of the default mode network (DMN), a common resting state network (RSN). The source localization results for the alpha band in patients showed unilateral activation of theinsula. The insula is an area commonly activated during pain processing2.

Conclusions: These results suggest that resting state EEG sources differ between healthy controls and patients with SCD. Healthy controls revealed prefrontal cortex activity associated with the alpha band, whereas patients had insula activity related to the alpha band. The prefrontal cortex activity in controls is most likely linked to the DMN, as this RSN has been associated with alpha band as well3. Insula activity observed in patients is most likely a result of their chronic pain. These differences reflected in the EEG signal are potential biomarkers of chronic pain and can be utilized to develop an objective measure of pain.References:1. He, B., Yang, L., Wilke, C., Yuan, H., 2011. Electrophysiological Imaging of Brain Activity and Connectivity #x2014; Challenges

and Opportunities. IEEE Trans. Biomed. Eng. 58, 1918–1931. doi:10.1109/TBME.2011.21392102. Apkarian, A.V., Bushnell, M.C., Treede, R.-D., Zubieta, J.-K., 2005. Human brain mechanisms of pain perception and regulation in

health and disease. Eur. J. Pain 9, 463–463. doi:10.1016/j.ejpain.2004.11.0013. Mantini, D., Perrucci, M.G., Gratta, C.D., Romani, G.L., Corbetta, M., 2007. Electrophysiological signatures of resting state

networks in the human brain. Proc. Natl. Acad. Sci. 104, 13170–13175. doi:10.1073/pnas.0700668104

Funding: NIH U01-HL117664 and NSF IGERT DGE-1069104.

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Classification of Tonic Pain and Rest Conditions using EEG DataVishal Vijayakumar1, Michelle Case1, Clara Huishi Zhang1, Bin He1

1. University of Minnesota, USA

Background: Chronic pain is a major health issue in the United States. The gold standard for measuring pain in the clinic is by self-report. This method is subjective and unreliable, which leads to sub-optimal pain treatment. We want to develop an unbiased and objective method to quantify pain reliably for chronic pain patients. In order to accomplish this goal, we studied pain responses to tonic thermal stimulation using Electroencephalography (EEG) in healthy subjects. EEG features were used to develop a classifier that could differentiate between high and low pain. Moreover, the top discriminative features can be used to assess EEG sources of activation that will reveal more details of the neurophysiology of tonic pain.

Methods: High-density 64 channel EEG was used to record neural responses to tonic thermal pain in healthy subjects. The thermal stimulus was delivered by a thermode placed on the dorsum of the wrist. The tonic thermal stimulus was applied for 30 seconds and followed by a rest period. This paradigm was repeated ten times over each trial. A tonic stimulus was used to better reflect the neural response of clinical chronic pain1. Independent Component Analysis (ICA) was initially used to remove artifacts from the EEG signal. Time-frequency transformations were applied to the cleaned Independent Components (IC) to assess the relative contribution of each IC to a particular frequency band. These contribution scores were then used as features for a Support Vector Machine (SVM) classifier2

with a polynomial kernel to distinguish between trials labelled as “pain” and “rest”.

Results: Initial runs of the classification algorithm show that the features used can discriminate between pain and resting states. The algorithm was run on neural responses from five subjects with stimulation between 40˚C and 46˚C. Preliminary results for the Area Under Curve3 (AUCs) of two out of the five subjects are shown below:

Conclusions: The above figure shows that classification accuracy is proportional to the degree of pain endured by the subject. Moving forward, the most informative features can be analyzed to find the frequency bands most prevalent in tonic pain responses, potentially unravelling the time courses and scalp topologies of ICs that contribute the most to those frequency bands. A successful classifier of tonic pain provides a foundation to developing an objective pain quantification method for chronic pain patients.References:1. Nir et al. 2012. “Tonic pain and continuous EEG: Prediction of subjective pain perception by alpha-1 power during stimulation and

at rest”2. Schulz et al. 2012, “Decoding an individual’s sensitivity to pain from the Multivariate analysis of EEG data”3. Mason et al. 2007, “Areas beneath the relative operating characteristics (ROC) and relative operating levels (ROL) curves:

Statistical significance and interpretation”

Funding: NIH U01-HL117664 and NSF IGERT DGE-1069104.

Figure 1: Comparison of Area Under Curve (AUC) for two subjects subjected to low and high pain trials

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Title: Can short-interval intracortical inhibition be modulated by low frequency repetitive transcranial magnetic stimulation

Authors: Mo Chen1, Teresa J. Kimberley2

Affiliations:1. University of Minnesota, Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab2. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical

Therapy and Rehabilitation Science

Background: Transcranial magnetic stimulation (TMS) is widely used as a non-invasive test of cortical excitability of the motor cortex. One paired-pulse method known as the short-interval intracortical inhibition (SICI) is used to measure intracortical inhibition. It involves delivering a subthreshold conditioning stimulus followed by a suprathreshold test stimulus at interstimulus intervals (ISIs) of 1 to 5 ms. The motor-evoked potential elicited by SICI is inhibited compared to that elicited by single test pulse alone. How SICI response modulated following neuromodulation intervention, i.e. low-frequency repetitive transcranial magnetic stimulation (rTMS), has been reported with inconsistent results of increased (Modugno et al. 2003), unchanged (Fierro et al. 2010) and decreased (Khedr et al. 2004) response. This study aimed to determine how SICI response modulates following 1-Hz rTMS with a comprehensive ISI span curve analysis.

Methods: A two group single-blind, pre-/post-test design was used. 25 participants (15 females, age 25.28±5.47) were recruited and divided into two groups: real (N=15) and sham (N=10). The modulation was 900 single-pulse subthreshold (90% of RMT) 1-Hz rTMS delivered by a figure-of-eight coil. The sham group received sham intervention delivered by sham coil. During the pre- and post-tests, participants resting motor threshold (RMT), 1mV threshold were determined. Then 15 trials of SICI with different ISIs (1.0 ~ 4.0 ms, increment, 0.2ms), 20 trials of single-pulse and cortical silent period (CSP) data were collected for pre and post comparison. Mixed model ANOVA was used to test the CSP difference between the two groups with an interactive factor of time (pre and post intervention). Student’s t-test was used to evaluate the pre-/posttest difference for each ISI within groups.

Results: There were significant interactions between groups for CSP (pre/post, p<.0001 and group*time, p=0.0015) meaning CSP was significantly modulated (increased due to inhibitory effect) by the both interventions (real and sham) and there was a difference between the two interventions: real intervention increased CSP to a greater extent than sham. T-tests on SICI did not demonstrate any difference between pre- and post-tests in either group, meaning SICI did not modulated by the intervention at any ISI. Further individualized analysis results will also be reported mainly focusing on the individual optimal ISI (the ISI gave the most inhibitory effect).

Conclusions: SICI may not be modulated by low-frequency subthreshold rTMS according to the results demonstrated in this study. Further parameter setting of SICI needs to be explored i.e. conditioning intensity curve.References:

Fierro B, De Tommaso M, Giglia F, Giglia G, Palermo A, Brighina F. Exp Brain Res. 2010;203:31–38

Khedr EM, Gilio F, Rothwell J. Clin Neurophysiol. 2004;115:1259-1263

Modugno N, Curra A, Conte A, Inghilleri M, Fofi L, Agostino R et al. Clin Neurophysiol. 2003;114:2416-2422

Funding: This study is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114.

Figure 1. Short-interval intracortical inhibition inter-stimulus interval comparison. Upper: real group pre- and post-tests comparison. Lower: real group pre- and post-tests comparison. No significant difference was found at any ISI although in the real group, the post ISI curve is higher than pre.

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Title: Laryngeal motor cortex excitability assessment using transcranial magnetic stimulationAuthors: Mo Chen1, Rebekah L. Schmidt2, Cecilia N Prudente2, George Goding3, Teresa J. Kimberley2

Affiliations:1. University of Minnesota, Institute for Engineering in Medicine, Non-invasive Neuromodulation Lab2. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical

Therapy and Rehabilitation Science3. University of Minnesota, Department of Otolaryngology-Head and Neck Surgery

Background: Transcranial magnetic stimulation (TMS) has been widely adopted to assess the motor cortex excitability from peripheral muscle recordings. However, using intrinsic laryngeal muscle targets, such as the thyroarytenoid (TA), to evaluate the excitability of the laryngeal motor cortex (LMC) has been difficult due to: lack of laryngeal muscle access using surface electrodes, difficulties verifying LMC vs peripheral nerve muscle responses, and large stimulation artifacts interfering with EMG recordings.

Methods: To address the aforementioed challenges, we developed a method to assess the excitability of the LMC using TMS. Fine-wire bipolar electrodes were inserted to record bilateral TA muscles’ responses to single pulse TMS stimuli delivered to the LMC in both hemispheres. In contrast, ipsilateral peripheral responses to stimulation over the mastoid, where the vagus nerve exits the skull, were compared with central responses in two healthy exemplar participants (both are females with the age of 42 and 49 respectively).

Results: With cortical stimulation, bilateral motor evoked potential (MEP) peak responses occurred around 12 ms followed by a silent period. The cortical silent period (CSP) ended at different times in the subjects tested: between 24.38 ms and 51.09 ms in the left and right TA muscles following cortical stimulation to either hemisphere as demonstrated in Figure 1. There was a 5~7 ms difference in peak MEP latency between the peripheral and cortical responses and the CSP only occurred with cortical stimulation.

Conclusions: The essential confirmation of cortical vs peripheral stimulation was provided by difference in the MEP latencies. The custom hardware, procedural design and setup solved the stimulation artifact problem making it possible to acquire an EMG signal from the TA muscles using fine-wire electrodes. This method will enable investigators to use TMS to study the LMC excitability changes and reveal the pathophysiology of the neurological disorders that affect TA muscles, such as spasmodic dysphonia and TA tremor. The methodology has application to other muscles of the head and neck not accessible using surface electrodes.

Funding: This study is a part of the National Institute of Communication Disorders and Deafness, National Institutes of Health (NIH) funding “The Pathophysiology in Spasmodic Dysphonia” (R21DC012344). This study is also supported by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114.

Figure 1. Bilateral TA MEP responses to right cortical stimulation during voice production in one participant. A: 50 individual traces of left TA responses to right cortical stimulation; B: 50 individual traces of right TA responses to right cortical stimulation; C: CSP from the left TA with right cortical stimulation (offset at 32.34ms); D: CSP from the right TA with right cortical stimulation (offset at 35.31ms). The stimuli were delivered at 0 ms. TA: thyroarytenoid. CSP: cortical silent period. MEP: motor evoked potential

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Title: Reinforcement learning for phasic disruption of pathological oscillations in a model of Parkinson’s disease

Authors: Logan L Grado1, Matthew D Johnson1, 2, Theoden I Netoff1

1Graduate Program in Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA2Institute for Translational Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455, USA

Affiliations:1Graduate Program in Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA2Institute for Translational Neuroscience, University of Minnesota, Minneapolis, Minnesota, USA

Background: Deep Brain Stimulation (DBS) is an effective therapy for symptoms of medication-refractory Parkinson’s Disease (PD). However, achieving an optimal therapeutic benefit for a given patient is challenging because many parameters must be evaluated, including which contacts to stimulate through, voltage or current amplitude, pulse width, stimulation frequency, and more. Current programming approaches rely on a trial-and-error approach, which is time consuming and often inefficient; resulting in compromises between increasing therapeutic benefit, lowering power consumption, and reducing side effects. In particular, all current DBS leads are programmed using a constant stimulation frequency, usually around 130 Hz. In this study, we have created an automated system capable of learning online, through trial and error, which phases (i.e. times) are best to stimulate to reduce pathological oscillations in silico.

MethodsWe developed our algorithm in the context of a biophysically realistic mean-field model of the basal ganglia-thalamocortical system [1], in which structure and parameters are closely based on experimental results, physiology, and anatomy. The model is capable of emulating both Parkinsonian and healthy sates. We created a Sarsa(λ) Reinforcement Learning Agent to adaptively learn the best sequence of stimulations to reduce pathological oscillations. An artificial neural network with Gaussian activation units was used to learn the value function from past experience and predict the reward of all available actions in any given state.

ResultsAfter training on the model, the agent was able to learn that certain phases of the oscillation were better to stimulate in, and to learn the value function over the state space. Additionally, the agent was able to learn sequences of actions to knock the model out of high-amplitude beta oscillations.

Conclusions We created an adaptive closed-loop algorithm capable of learning on-line how to optimally stimulate to reduce beta power in a computational model of the parkinsonian basal ganglia.This algorithm has the potential to learn optimal stimulation patterns to reduce symptoms of other brain disorders in which pathological oscillatory features emerge.

References[1] S. J. van Albada and P. a Robinson, “Mean-field modeling of the basal ganglia-thalamocortical system. I

Firing rates in healthy and parkinsonian states.,” J. Theor. Biol., vol. 257, no. 4, pp. 642–63, Apr. 2009.

FundingResearch supported by the Systems Neuroengineering NSF IGERT Program (DGE-1069104)

Figure 1. Difference between the expected reward of stimulating vs reward of not stimulating in any given state of the oscillation

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Title: Multivariate Pattern Analysis of fMRI Data Reveals the Discrete Neural Signature of Target-Specific Deep Brain Stimulation. .

Authors: Shinho Cho1, Paola Testini1, Megan Settell1, Hang Joon Jo 1, Paul Min1,2 , Kendall H. Lee1,2

Affiliations: 1. Department of Neurologic Surgery; 2. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN

Background: Subthalamic nucleus (STN) DBS has been known to evoke non-motor effects. However, the underlying neural mechanism of the non-motor neuromodulatory effect evoked by STN has been poorly understood. We combined fMRI with a multivariate pattern analysis (MVPA) approach to investigate the non-motor effects of STN DBS by discriminating characteristic neural activation patterns induced by STN and nucleus accumbens/internal capsule (NAc/IC) DBS, which has been an effective target for psychiatric diseases.

Methods: We performed STN (n=7) and NAc/IC (n=7) DBS-fMRI in a large swine population. A total of 25 ROIs were defined based on the significance of BOLD signal change across multiple cortices and lobule. We then applied a pattern classifier (Fisher’s Linear Discriminant Analysis) to discriminate combined BOLD patterns from distributedROIs. The analysis included whole-brain classification (25 ROIs), cortex-based classification (5 clusters), and principle feature set (5 ROIs). We also used a feature selection algorithm with the Sequential Feature Selection. The mean classification accuracy was cross-validated by K-folds (n=10) and cross-subjectively validated to generalize the results.

Results: We found that whole-brain classification with 25 ROIs yielded over 90% mean classification accuracy, suggesting STN and NAc/IC induced a very distinctive pattern of large-scale neural network modulation. To identify which brain regions contributed to this classification, we divided the ROIs into anatomical and/or functional clusters (association, limbic, sensorimotor, and insular cortices, and thalamus), and conducted cortex-based classification of ROIs that belong to the same cortex/lobe across STN and NAc/IC DBS. The men accuracy reached approximately 70% for each functional system; this suggests that the discrete neural signatures of STN and NAc/IC DBS are mainly represented in three networks (association, limbic, sensorimotor). Furthermore, the feature selection procedure showed that five ROIs (prefrontal cortex, posterior caudate, laterodorsal thalamus, dorsal anterior cingulate, and premotor cortex) played a pivotal role in classifying the activation patterns of STN and NAc/IC DBS, reaching 90% average classification accuracy.

Conclusions: We concluded that discrete neural patterns of STN and NAc/IC DBS were mainly defined by the signal pattern evoked in three areas: the association cortex, the limbic lobe, and the sensorimotor cortex. Multivariate pattern analysis could both classify the DBS target-specific neural signatures, and elucidate which brain regions identify such signatures. Our results suggest that although both STN and NAc/IC DBS have been known to induce psychiatric effects, there is considerable difference in the activation patterns associated with stimulation of these two targets.

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16-channel automatic multiple electrode tester (MET16) for implanted cortical microelectrodes

Philip Troyk1,2, Zhe Hu2, Glenn DeMichele2

1. Department of Biomedical Engineering, Illinois Institute of Technology, Chicago IL; 2. Sigenics Inc., Chicago IL;

Background: Currently there is no simple method to check the “health” of an implanted microelectrode array and certain types of failures are not well-revealed by the commonly used 1kHz single-point impedance measurement, thus making it difficult to assess whether loss of neural signals, or diminishing of stimulation responses, are due to array failures, or changes in the underlying neural network. Cyclic voltametry (CV), electrochemical impedance spectroscopy (EIS) and electrode pulsing measurements,can provide information about the electrochemical nature of the electrode/neural tissue interface and other array failures. The shapes of the EIS magnitude and phase curves can serve as important signature patterns for comparing supposedly identical electrodes. When used in combination, CV and EIS can easily reveal the most common cause of implanted electrode array failure: broken electrical connections.Unfortunately, CV and EIS are usually performed using single-channel bulky bench-top potentiostat instruments , and comprehensive measuring of a 16-channel array can take up to 150 minutes. We have developed the MET16 to be a CV/EIS/pulsing instrument that can simultaneously characterize 16 electrodes in 5-10 minutes. In this study, we measured a 32-microelectrode array (manufactured by Microprobes for Life Sciences - MLS) newly implanted in the cortex of a macaque monkey.

Methods: In accordance with an approved animal protocol at Northwestern University, and immediately following implantation, one MET16 was used to measure CV and EIS for all electrodes within the 32-microelectrode array within 10 minutes.

CV curves from 32 implanted electrodes. Vert scale: +/- 10nA, 5nA/div; Horiz scale: -0.6V - +0.8V, 0.2V/div

Results: Looking at the CV data, notable variations exist between “identical” electrodes, data for electrodes E8, E14, E18, E20, E29, indicating larger surface areas than all others. The flat CV curves for electrodes E1, E2, E17, E32 reveal open circuits. Subsequent measurements will be made to track the “health” of the array as experimental testing proceeds over the next 2-3 months.

ConclusionsThe post-surgery evaluation of the implanted microelectrode array by the MET16 produced valuable information about the initial state of the electrode array. The data presented here will serve as our baseline. Using future scans, we will be able to observe the long-term drift, and failure, of electrodes in this chronic implant. We expect that analysis of these long-term data will lead to the discovery of root-cause failure mechanisms and illuminate ways to improve the reliability of these implanted systems.

FundingThis work was funded by DARPA contract N6600112C-4055, and internal Sigenics R&D.

E1 E2 E3 E4

E5 E6 E7 E8

E9 E10 E11 E12

E13 E14 E15 E16

E17 E18 E19 E20

E21 E22 E23 E24

E25 E26 E27 E28

E29 E30 E31 E32

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Vagus nerve stimulation combined with rehabilitation for the upper extremity after strokeCecilia N. Prudente1, Teresa Bisson1, Danielle Kline1, Kate Frost1, Stephen J. Haines2, David Pierce3,

Navzer Engineer3, Teresa J. Kimberley1

1. Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy and RehabilitationScience, University of Minnesota, US; 2. Department of Neurosurgery, University of Minnesota, US;

3. Microtransponder, Inc., US

Background: Animal studies have shown that pairing vagus nerve stimulation (VNS) with movement training induces movement-specific neuroplasticity in the motor cortex, resulting in improved forelimb function. A recent randomized controlled clinical pilot study demonstrated the safety and feasibility of using VNS in humans who had an ischemic stroke [1]. Currently, a follow-up multicenter double-blinded randomized controlled trial is underway to determine the effects of VNS paired with rehabilitation on upper extremity function after chronic stroke. The purpose here is to present preliminary data from our site.

Methods: Three subjects (2 males, 63±10.5 years old) with moderate to severe upper limb impairment have participated in the study. VNS implantation involved placement of cuff electrodes on the left vagus nerve in the left carotid sheath. Each electrode’s lead was attached to a pulse generator implanted in the left pectoral region. Participants were randomized into two groups: VNS plus rehabilitation or sham VNS plus rehabilitation (control). Subjects completed high-repetition, activity-specific rehabilitation for 2 hours/day, 3 days/week, for 6 weeks. In the VNS group, movements were paired with 0.5-second burst of VNS at 0.8 mA. The stimulation was manually triggered by the physical therapist while the patient performed a task. For the control group, the VNS bursts were set to zero mA. Each therapy session involved ~300 repetitions of challenging hand and arm movements. Upper limb function was assessed at: baseline 1, baseline 2, post-implant, mid-treatment, and post-treatment (1, 7 and 30 days after therapy). Outcome measures included the Upper Extremity Fugl-Meyer Assessment (UEFM), Wolf Motor Function Test (WMFT), and Box and Block Test (B&B). All preliminary analyses are descriptive due to the ongoing nature of this study and small sample size.

Results: All enrolled subjects completed therapy (VNS group: n=2; Control group: n=1) and no adverse events were reported. At post-treatment 1, UEFM scores improved in both groups (VNS: 23.8% and 36.8%; control: 26.5%). WMFT scores also improved (VNS: 16%, 20.8%; control: 8.6%), whereas the B&B test showed mixed effects (VNS: 10.8%, 0%; control: 91.7%). All participants are currently in long-term follow-up.

Conclusions: Rehabilitation combined with VNS or sham stimulation improved motor function. However, VNS plus rehabilitation may specifically improve tasks measured by the WMFT more than rehabilitation alone. Thus, VNS remains a potentially beneficial adjunct to rehabilitation and the completion of long-term follow-up and more subjects is warranted. References:1. Dawson et al. Safety, feasibility, and efficacy of vagus nerve stimulation paired with upper-limb rehabilitation after ischemic stroke.Stroke, 2016;47(1):143-50.

Funding: Microtransponder, Inc.

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On-Chip Data Compression for Large-Scale Neural RecordingTong Wu, Wing-kin Tam, Zhi Yang

University of Minnesota Twin Cities, MN, USA

Background: Large-scale neural recording using electrodes has gained increasing popularity to understand the neural circuits. The recorded voltage potentials are contributed by neurons in a local proximity of the electrode tips as well as unresolved activity and noise. A spike sorting process can be used for data compression and analysis of single-unit activity, such that a low-power wireless data link becomes possible to transmit information from a large number of channels. For example, the raw data rate from a 1000-channel neural recorder with 40kHz sampling rate and 16-bit digitization precision is 600Mbps. With on-chip data compression, it is possible to reduce the data rate to 60kbps-6Mbps that is feasible for wireless transmission. This requires efficient and intelligent on-chip neural signal processing.

Methods: We developed new circuits for large-scale recording and stimulation. Here, we propose processing circuits that can compress neural data. The neural data are split into three components including field potentials, multi-unit activity, and spikes. For field potentials, the spatial wavelength is several hundred microns thus can be easily compressed. For multi-unit activity, we propose an EC-PC algorithm that can convert the multi-unit activity into a spiking probability map for decoding. For spikes, we have developed power- and area-efficient circuits that can perform multichannel spike detection and sorting. Our circuits are designed in either 65nm process for standalone processing or 130nm process for integrated recording and stimulation.

Results: With our processing circuits, the data rate can be compressed by 100-10,000 times, depending on if transmitting binary data, spike templates, or waveforms. The decoding accuracy remains with the compressed data in preliminary experiments.

Conclusions: We propose an approach for on-chip data compression that consists of both analog and digital signal processing. It allows 100 or even 10,000-fold data compression without losing much information.

Figure 1. Experiment results of the EC-PC spike detection hardware. (a) 8-channel EC-PC spiking probability maps. (b) 8-channel time-series spike data. (c) Trajectory of the joystick movement in the monkey decoding experiment. (d) Comparison of decoding accuracy between different spike detection methods. EC-PC: EC-PC decomposition; Median: median threshold; NEO: Nonlinear Energy Operator; RMS: threshold based on root-mean-square method; CWT: continuous wavelet transform. The number behind NEO and RMS are the threshold level that produce the highest accuracy. NEO was test from 10 to 12 and RMS was tested from 3 to 5 of the threshold level (a) The decoding accuracy when all channels was used (e) Comparison of firing rate estimation obtained by EC-PC and amplitude threshold, where the result of EC-PC is more consistent and easier to classify.

Funding: University of Minnesota start-up fund.

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Title: Tactile sensor development for upper limb prosthesesAuthors: Kory Jenkins1, Rusen Yang1

Affiliations: 1. University of Minnesota, USA

Background: A neural interface between tactile sensors and the peripheral nervous system has been shown to provide some tactile sensation to upper limb amputees [1]. This has encouraged much recent interest in the development of artificial skin for sensory restoration applications. The objective of this work is to develop a highly sensitive tactile sensor for prosthetic applications based on zinc oxide nanowires and the piezotronic effect.

Methods: Nanostructures such as zinc oxide nanowires are well-suited for use in tactile sensors due to their favorable electrical and mechanical properties. The working principal, piezotronics, relies on the piezoelectric and semiconducting properties of zinc oxide to control charge carrier transport across the device. Additionally, zinc oxide can form a Schottky contact with high work function metals such as gold, giving such devices high sensitivity to applied strains. ZnO nanowires can be synthesized through the scalable hydrothermal method, or by chemical vapor deposition. The resulting nanowires are single crystal, making them mechanically robust and resistant to fatigue failure. The sensor design is informed by first principles and finite element methods and device fabrication may be carried out using conventional microfabrication techniques.

Results: Finite element analysis suggests that the proposed tactile sensor design will be highly sensitive to contact forces in the nanonewton range. FEA results will be used to inform ongoing device fabrication work and explore the effects of device design on sensor performance under various loading conditions.

Conclusions: This work outlines the design and finite element analysis of a novel piezotronic tactile sensor. Simulation results suggest that the proposed sensor will be able to detect a variety of contact forces at the nanonewton level. The development of novel artificial skin architectures will facilitate the advancement of sensory restoration systems for prosthetic applications. References:

[1] Tan, Daniel W., et al. "A neural interface provides long-term stable natural touch perception." Science translational medicine 6.257(2014): 257ra138-257ra138.

Funding: NSF IGERT grant DGE-1069104, NSF ECCS-1150147, Land Grant McKnight Professorship (R. Yang). Parts of this work were carried out in the Characterization Facility, University of Minnesota, which receives partial support from NSF through the MRSEC program

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Title: Designing a Multi-Electrode Array Compatible with Ultrahigh Field MRI Corey Cruttenden1, Hannes Wiesner2, Xiao-Hong Zhu2, Wei Chen2, and Rajesh Rajamani1

1. Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN, USA; 2. Center for MagneticResonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.

Background: The publication of Neurophysiological Investigation of the basis of the fMRI signal initiated years of debate on the true neural correlates of the blood-oxygen-level-dependent (BOLD) signal [1]. Subsequent multi-modal electrophysiology / fMRI studies have uncovered a substantial number of correlations regarding neurovascular coupling. Simultaneous multi-modal experiments have been particularly useful, but these studies often suffered from a drastic mismatch between the modalities owing to relatively low spatial resolution of fMRI and severe imaging artifacts induced by metal electrode(s).

We are developing a micro-scale multi-electrode array (MEA) for use in ultrahigh field MR imaging. Specifically, our probes will utilize photosensitive polymer substrates and conductive materials with a desirable balance of magnetic and electrochemical properties matching the brain tissue. We hope that this technology will enable simultaneous electrophysiology and fMRI with extremely high resolution, reducing the spatial resolution mismatch between modalities and providing additional insight into the mechanisms of neurovascular coupling.

Methods: Magnetic field distortions must be minimized to achieve high quality fMRI. However, the proposed simultaneous multi-modal study requires a foreign object (the MEA) in the brain region of interest (ROI). The resulting field distortion will be proportional to the difference in magnetic susceptibility between the object and surrounding medium, as well as the magnetic field strength. The susceptibility difference between water and silicon (the conventional MEA substrate) is 4.85 ppm [2]. We are using a polymer substrate in place of silicon to reduce the susceptibility difference to within 1 ppm [3]. Additionally, we are using carbon nanotubes (CNT) to interface with the extracellular medium, because their high surface area provides low electrochemical impedance, excellent SNR, and high biocompatibility. While CNT is also diamagnetic, we predict that the substrate choice will play a larger role in minimizing susceptibility artifacts, because the substrate constitutes the majority of the device volume. The fabricated MEAs will be examined through in vitro imaging studies at high field and tested for their ability to record neural activity in vivo.

Results: We have devised a strategy to create MEAs with magnetic properties closely matched to biological tissue using established microfabrication techniques. Initial processing steps are underway (see Figure 1) and in vitro imaging studies are soon to follow.

Conclusions: The novel MR-compatible MEA design should enable us to investigate neurovascular coupling through simultaneous electrophysiology and fMRI with high spatial resolution. References: [1] N. K. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann.Neurophysiological investigation of the basis of the fMRI signal. Nature,412(6843):150–157, July 2001.[2] J. F. Schenck. The role of magnetic susceptibility in magnetic resonanceimaging: MRI magnetic compatibility of the first and second kinds. Medicalphysics, 23(6):815–850, 1996.[3] M. C. Wapler, J. Leupold, I. Dragonu, D. von Elverfeld, M. Zaitsev, andU. Wallrabe. Magnetic properties of materials for MR engineering, micro-MR and beyond. Journal of Magnetic Resonance, 242:233–242, 2014.

Funding: This work is supported in part by the Institute for Engineering in Medicine (IEM) Group Grant at the University of Minnesota, the University of Minnesota MnDrive RSAM Initiative Grant, NSF IGERT Grant DGE-1069104, NIH grants RO1 NS057560, RO1 NS070839, R24 MH106049, P41 EB015894, P30 NS5076408, and the W.M. Keck Foundation.

Figure 1. MEA polymer substrates patterned by photolithography on a 4” silicon wafer. Chemical etching will be used to undercut and release the devices.

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Intercostal Cryoanalgesia in the Ovine ModelAdam W. Cates1, Laurie A. Yunker1, Daniel Lafontaine1, Christina Gross2, Lynette Phillips2, Bob Trusty1,

Tamer Ibrahim1, Steven F. Bolling3

1. AtriCure, Inc., Minnetonka, MN; 2. American Preclinical Services, Minneapolis, MN; 3. University of Michigan,Ann Arbor, MI.

Background: Intercostal cryoanalgesia is achieved by cryoablating the intercoastal nerve(s) which provides temporary pain relief following thoracotomy. Freezing the intercostal nerve induces Wallerian degeneration where the nerve axon degenerates from the point of freeze to the end organ but the nerve perineurium and epineurium remain intact. Subsequently, the nerve axon regrows through the intact structures to re-innervate the end organ, restoring sensation and function1. This study assessed the feasibility of using an ovine model for evaluating intercostal cryoanalgesia by comparing 1 and 2 min freezes.

Methods: A sternotomy was performed on 2 sheep (F, 66 and 68kg) and cryoablation was applied to the 3rd-5thintercostal spaces on both the right and left thorax. A N2O cryoprobe tip (2-3 cm) was positioned directly on the nerve near the margin of the innermost intercostal muscle and the posterior internal intercostal membrane. Freeze duration of 1 or 2 min was randomized to either the right or left intercostal spaces. A sham freeze was performed in one of the 6th intercostal spaces by placing the probe for 1 or 2 min without applying cryoablation to isolate effects of mechanical force. Serial skin pinch-reflex tests were performed for 4 weeks in each thoracic region to assess loss and return of motor response as a surrogate for sensory function because the intercostal nerves include both motor efferent and sensory afferent nerves. At 35d, animals were euthanized and nerves were H&E stained for observation at 3 locations: the freeze location, proximal (towards the spine), and distal (towards the sternum) to the freeze site.

Results: Pinch reflex was absent in each thoracic region but gradually returned by 35d, suggesting successful cryoanalgesia. Histology demonstrated nerve changes such as myelin sheath swelling, vacuolation and degeneration with axonal loss and sheath infiltration by lipid-filled phagocytes at freeze sites and sites distal to the freeze, but not proximal to the freeze (see Figure). The histological results, consistent with Wallerian degeneration, confirmed successful cryoanalgesia in 5/6 intercostal spaces with 1 min freezes and 6/6 intercostal spaces with 2 min freezes.No nerve changes were observed with the sham freezes, indicating no effect of mechanical trauma from the probe.

Conclusions: The ovine model is feasible for preclinical evaluation of intercostal cryoanalgesia techniques, and successful intercostal cryoanalgesia was assured with 2 min freezes. These findings are encouraging for intercostal cryoanalgesia as a pain management option with cardiac and thoracic surgeries. References:1 Trescott. Cryoanalgesia in Interventional Pain Management. Pain Physician. 2003;6:345-360.

Funding: AtriCure, Inc.

A. Proximal site B. Freeze site C. Distal siteFigure. H&E stained cross-sections of an intercostal nerve at a site proximal (A) to the freeze site, at the freeze site (B), and distal (C) to the freeze site. Arrows indicate degenerative nerve fibers.

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VP+DCVP

Title: Safe Direct Current Stimulation Increases the Dynamic Range of Head Velocities Encoded by the Vestibular Prosthesis

Authors: Yu (Erin) Zheng, Dilawer Singh, Gene Y. Fridman Affiliations: Johns Hopkins University, Department of Otolaryngology Head and Neck Surgery, Department

of Biomedical Engineering BackgroundThe vestibulo-ocular reflex (VOR) stabilizes vision in response to head motion. The main components responsible for detecting head rotation are the three semi-circular canals (SCCs) located in each inner ear. SCCs in normal ears are bi-directional sensors of head rotation: they up-modulate vestibular nerve afferent activity above spontaneous firing rates during ipsilateral head rotations and down-modulate activity below spontaneous levels during contralateral rotations. [1] Individuals with bilateral vestibular deficit (BVD) have significant loss of vestibular sensation which causes destabilization of vision during head motion resulting in dizziness and disequilibrium and could be aided by a multichannel vestibular prosthesis (MVP).[2] An MVP modulates the activity of surviving afferent fibers based on head motion detected by gyroscopes and encodes it with pulsatile stimuli delivered to the vestibular nerve. However, the range of head velocities the MVP evokes is small. One hypothesis that explains this unresolved problem is that the vestibular nerve afferents maintain spontaneous activity and delivering pulses to encode head rotation can increase the firing rate but not decrease it below baseline.

MethodsSafe Direct Current Stimulation (SDCS) technology from our lab delivers ionic current to the vestibular nerve to suppress its spontaneous activity. [3] To conduct experiments, chinchillas have electrodes surgically placed in the SCCs, and a fluorescent marker is attached to the eye. Software developed by our lab controls the MVP to stimulate afferent fibers using sinusoidally modulated pulse trains with varying pulse rates while the camera detects eye movement.

ResultsVestibular prosthesis experiments with (VP+DC) and without SDCS stimulation (VP) suggest improvement 4.5±2.5 for movements in the direction of the prosthesis and 3.3±1.6 for head movements away from the prosthesis when SDCS was used to suppress spontaneous neural activity. The figure shows the results from four separate experiments.

ConclusionsOur experiments suggest a method for significantly improving the dynamic range of head velocities that can be encoded by the vestibular prosthesis. While the explanation for why the dynamic range improves for head motion away from the implant appears clear based on the spontaneous activity of the vestibular afferents, the improvement of the dynamic range of head motion toward the implant encoding is not easily explained. We are hypothesizing that the neural processing that interprets the input from the vestibular afferents has a spontaneous activity set-point that the brain easily adapts to, but the fundamental properties of the network remain unchanged.

References[1] Fetter, M. (2007) Vestibulo-Ocular Reflex. Developments in Ophthalmology, 40, 35-51.[2] Della Santina, Charles, et al. (2007). A Multichannel Semicircular Canal Neural Prosthesis Using ElectricalStimulation to Restore 3-D Vestibular Sensation. IEEE Transactions on Biomedical Engineering, Vol.54, No. 6.1016-1030.[3] Fridman, Gene Y. (2013). Safe Direct Current Stimulation to Expand Capabilities of Neural Prostheses. IEEETransactions on Neural Systems and Rehabilitation Engineering, Vol.21, No. 2. 319-328.

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Effect of parkinsonism and deep brain stimulation on phase-amplitude correlations in macaque globus pallidus and motor cortex

David Escobar1, Luke Johnson1, Shane Neback1, Matthew Johnson2, Kenneth Baker1, Gregory F. Molnar1,Jerrold L. Vitek1

1. University of Minnesota, Department of Neurology, USA; 2. University of Minnesota, Department of BiomedicalEngineering, USA

Background: The correlation between the phase of low-frequency and the amplitude of high-frequency neural oscillations (phase-amplitude correlation, PAC) in the basal ganglia and motor cortex has been hypothesized to be an intrinsic biomarker of Parkinson's disease (PD) [1,2]. Human studies have also suggested that PAC in primary motor cortex (M1) decreases during deep brain stimulation (DBS) of the subthalamic nucleus (STN) and could be used as a feedback signal for closed-loop DBS systems [3]. In this study, we used two nonhuman primates to characterize changes in PAC within globus pallidus internus (GPi) and M1 after the induction of the PD state and during therapeutic STN- and GPi-DBS.

Methods: Two rhesus macaques were implanted in the STN and GPi with 8-contact DBS leads to record local field potentials (LFPs) and deliver electrical stimulation. A Utah array was implanted in the arm area of M1 to record LFPs. The parkinsonian state was induced by systemic injections of the neurotoxin MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine). Customized software was employed to quantify PAC based on LFP recordings in the awake state of the subjects.

Results:

1. PAC emerged in the PD state in different brain structures for each animal. In subject 1, PAC significantlyincreased in GPi but not in M1, whereas in subject 2, PAC increased in M1 only.

2. PAC was modulated by therapeutic stimulation of only specific brain targets. In subject 1, PAC in GPidecreased during GPi-DBS but not during STN-DBS. In subject 2, PAC in M1 decreased during STN-DBSbut not during GPi-DBS.

Conclusions:1. PAC in GPi and M1 of the studied animals could be a marker of the parkinsonian condition. However, the

location where PAC emerges is inconsistent between animals, suggesting that PAC biomarkers may varydepending on the subject or recording location.

2. PAC measures in GPi and M1 did not correlate with the improvement of motor signs during therapeutic DBSin STN and GPi respectively. This lack of correlation limits our ability to use PAC to directly quantify theimprovement of motor symptoms during stimulation in specific brain regions. Yet, the diverse PACmodulation patterns may be associated to the specific STN- and GPi-DBS mechanisms of action.

3. Future studies will evaluate whether PAC in individual sites may reflect abnormal coupling betweenstructures in the basal ganglia-thalamocortical network and how PAC measures can be used to increase theefficacy of DBS therapies.

References:

[1] C. de Hemptinne, E.S. Ryapolova-Webb, E.L. Air, P.A. Garcia, K.J. Miller, J.G. Ojemann, J.L. Ostrem, N.B. Galifianakis, and P.A.Starr, “Exaggerated phase–amplitude coupling in the primary motor cortex in Parkinson disease,” PNAS, 2013.[2] A.T. Connolly, A.L. Jensen, E.M. Bello, T.I. Netoff, K.B. Baker, M.D. Johnson, and J.L. Vitek, “Modulations in Oscillatory Frequencyand Coupling in Globus Pallidus with Increasing Parkinsonian Severity,” The Journal of Neuroscience, 2015.[3] C. de Hemptinne, N. C. Swann, J. L. Ostrem, E.S. Ryapolova-Webb, M. San Luciano, N. B. Galifianakis, P. A. Starr, “Therapeuticdeep brain stimulation reduces cortical phase-amplitude coupling in Parkinson's disease,” Nature Neuroscience, 2015.

Funding: National Institutes of Health grant N01 NS037019S; MnDRIVE Postdoctoral Fellowship in Neuromodulation.

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A Transient Model for Neuronal Oscillations Carlos A. Loza, Jose C. Principe

Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA

Background: Classical signal processing methods for neuronal oscillations, such as EEG and LFP, usually rely on the strong restrictive assumptions of stationarity and ergodicity. However, electrical potentials from the brain are well known for displaying statistical properties that vary over time giving rise to transient patterns [1]. Moreover, decomposition methods in the literature not only utilize these erroneous assumptions, but they also introduce processing windows that smear the temporal information encoded in the structure of the signal. We propose a transient model that poses a single EEG trace as the result of the noisy addition of reoccurring, transient events over time and frequency bands (Fig. 1). This enables to preserve the superior temporal resolution of EEG while incorporating additional features to the model, such as amplitude, frequency, duration, and modulation-based measures related to relevant phasic events. These measures can, consequently, be utilized to interpret behavior and stimuli encoding in the brain at a macroscopic level beyond single unit paradigms.

Methods: Sparse decomposition and dictionary learning [2] techniques are utilized in order to learn the relevant events directly from the EEG traces. The algorithms are completely window-free, data-driven and do not impose pre-defined templates, such as complex sinusoids or wavelets. In addition, based on the clinical interpretation [3] and local interaction of principal cells and interneurons, we restrict the possible extracted snippets to modulated, spindle-like shape patterns. This is not only neurophysiologically sound, but it also accelerates the convergence of the proposed techniques. Afterward, the extracted features are post-processed to extract relevant statistics. For instance, behavior and topographic discriminability is assessed by computing the statistical relevance values.

Results: The proposed framework is applied to BCI competition dataset III. The decomposition features preserve amplitude-based relevance (p = 2.68 x 10-8, p = 3.48 x 10-7) observed in similar studies. Furthermore, the novel joint amplitude-timing space provides discriminability over time by modeling the learned properties as samples from a continuous Gaussian Mixture Model.

Conclusions: We provide a transient model for neuronal oscillations where the relevant features are extracted automatically from single-channel EEG traces. In particular, the system does not assume stationarity and does not utilize pre-defined templates for the decomposition. This opens the door for further innovative analysis and processing where the superior temporal resolution of the phasic events can be mapped to spike activity and fine-tuned behavioral tasks. In addition, the findings provide richer information than the classical amplitude-based decomposition methods; hence, allowing multivariate EEG analysis. References: [1] G. Buzsaki and A. Draguhn, “Neuronal oscillations in cortical networks,” science, vol. 304, no. 5679, pp. 1926–1929, 2004.[2] M. Aharon, M. Elad, and A. Bruckstein, “K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation,”Signal Processing, IEEE Transactions on, vol. 54, no. 11, pp. 4311–4322, 2006.[3] E. Niedermeyer and F. L. da Silva, Electroencephalography: basic principles, clinical applications, and related fields. LippincottWilliams & Wilkins, 2005.

Funding: Michael J. Fox Foundation, Grant 9558.

Fig. 1. Transient Model for EEG. A single-channel EEG recording can be regarded as the noisy addition of transient, finite, reoccurring events over time and different frequency bands.

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MEG Source Imaging of Epileptic Activity Shuai Ye1, Abbas Sohrabpour1, Wenbo Zhang2, Bin He1,3

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Minnesota Epilepsy Group, USA; 3.Institute for Engineering in Medicine, University of Minnesota, USA

Background: Most healthy and pathological processes in the brain involve distributed networks. In order to effectively modulate pathological networks, the underlying dynamics of such networks need to be understood and furthermore, monitored during the administration of the neuromodulatory therapies [1]. Electromagnetic source imaging (ESI) provides high temporal resolution of underlying brain sources which is necessary to study and monitor dynamic neural networks. ESI is used extensively in monitoring many neurological conditions, including epilepsy, the most prevalent neurological disorder. MEG provides high temporal resolution solutions (~ 1 ms). ESI can provide estimations of the location of epileptic brain network nodes as well as inter-connections and dynamics of the epileptic network. This information can be used to guide neuromodulation and other therapies for treating epilepsy and other neurological disorders.

Methods: In this study, MEG was recoded from patients suffering from focal epilepsy. Inter-ictal spikes (IIS) were selected from the recordings of epileptic patients and the underlying epileptic sources were estimated. This was realized through solving the inverse problem which is the process of estimating underlying brain electrical activity from noninvasive recordings such as MEG.148-channel MEG was recorded during IIS, as well assubjects’ structure MRI. The patients in this studywere considered for surgical resection as these patientswere not responding to anticonvulsant medications.The MEG recordings were monitored for IIS andaveraged IIS were input into the ESI algorithms toestimate underlying epileptic networks to determinethe onset zone of seizures and epileptic activity. Theresults were compared to clinical findings such assurgical resection (obtained from post-operationalMRI).

Results: The initial results indicate that source imaging results from MEG coincide well with the clinical findings. In the example presented in Fig.1, 14spikes were selected for analysis. The maximum of localization result fell inside of the resection area. Moreover, the identified source area was overlapping well (~60%) with the clinically resected zone.

Conclusions: Although, our study was performed in a specific neurological disorder, i.e. epilepsy, ESI is a powerful tool that can be used effectively to study and understand the location and inter-dynamics of the nodes of underlying brain networks. Such efficient tools shall provide useful information to guide interventional procedures such as surgery or neurostimulation [2]. ESI methods can be integrated with neuromodulation therapies in a closed-loop fashion to achieve better outcomes.References:[1]. E. Bullmore and O. Sporns, Nature Reviews Neuroscience, vol. 10(3), pp. 186-198, 2009. [2]. M. J. Morell et al., Neurology, vol. 77(13), pp. 1295-1304, 2011.

Funding: NSF DGE-1069104, NSF CBET-1264782, and a grant from IEM.

.

Fig. 1. One example of MEG source reconstruction.

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Development of Deep Brain TMS Coil: Triple Halo CoilPriyam Rastogi1, Ravi Hadimani2, 1, David Jiles1

1. Iowa State University, USA; 2. Virginia Commonwealth University, USA.

Background: Transcranial Magnetic Stimulation is a non-invasive stimulation technique which can be used for thetreatment of various neurological disorders by inducing electric field inside the brain. FDA has approved TMS forthe treatment of major depressive disorders and migraines by stimulating the outer part of the brain [1, 2]. TMS can also be used for stimulation of the deep brain regions to provide an alternative to surgical methods by developingdeep TMS coils. A multi-configuration coil, Triple Halo Coil (THC) has been developed to stimulate the deep regions of the brain which are below 7 cm from top of the head. THC has been used in combination with a “Figureof Eight” coil and a circular coil to enable deep brain stimulation.

Methods: SEMCAD X, a finite analysis tool, has been used for modelling and calculations of the magnetic and induced electric fields inside a heterogeneous head model [3]. MRI data of a 34 year old man was used to derive the heterogeneous head model. Comparison of the results of THC configuration with other coils such as Halo Coil (HC),commercial “Figure of Eight” and circular coils.

Results: The THC configuration with a top coil was used to stimulate the deep brain regions with a highermagnitude of magnetic field, maintaining the same magnitude at the top surface of the brain when compared with other coils. The values of the magnetic field at 10 cm below the head were 0.14 MA/m for THC configuration with “Figure of Eight” as the top coil, 0.089 MA/m for an “HC configuration with “Figure-of-Eight” as the top coil, 0.02 MA/m for a “Figure of Eight” coil by itself and 0.05 MA/m for a circular coil by itself. Stimulating the deep brainregions has shown to have beneficial effects on the neurological disorders, thus a THC configuration will provide clinicians with a new tool to treat deep brain neurological disorders.

Conclusions: There was an improvement of more than 7 times in the strength of the magnetic field, generated by aTHC configuration with the “Figure of Eight” coil at 10 cm below the vertex of the head when compared with the “Figure of Eight” coil alone. The use of “Figure of Eight” coil in combination with the THC helped to reduce thestimulation in the frontal lobe yet maintain a high electric field in the deep brain region.References:[1] MagVenture. FDA cleared TMS depression treatment from MagVenture n.d. http://www.magventure.com/en-gb/FDA-cleared-TMS-depression-treatment (accessed October 13, 2015)[2] FDA News Release. FDA allows marketing of first device to relieve migraine headache pain.http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm378608.htm (accessed March 1, 2016)[3] Schmid & Partner Engineering AG. SEMCAD X n.d. http://www.speag.com/products/semcad/intro/ (accessed September 11, 2015).

Funding: Galloway Foundation and The Carver Charitable Trust

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Title: Seizure suppression using a Linear Quadratic Gaussian controllerAuthors: Vivek Nagaraj1,, Andrew Lamperski3, Theoden I Netoff1,2

Affiliations: 1. Graduate Program in Neuroscience; 2. Department of Biomedical Engineering; 3. Department ofElectrical and Computer Engineering; University of Minnesota Twin-Cities, USA

Background: The closed-loop Responsive NeuroStimulator (RNS) device has helped some patients with intractableEpilepsies, however; many patients do not have complete seizure freedom1. One contributing factor to the inabilityof the RNS device to achieve full efficacy is the large stimulation parameter space that clinicians need to optimizeover. This work attempts to address this issue by presenting a novel automated closed-loop algorithm for seizurecontrol by selectively applying stimulation while minimizing total stimulation energy.

Methods: We used a computational model of Epilepsy (Epileptor2) to test the efficacy of the Linear QuadraticGaussian (LQG) controller. The Epileptor model is a mean-field model that reproduces the local field potential (LFP) activity within a seizure focus. We used a subspace system identification method to determine a mathematical modelof the Epileptor LFP data. The LQG controller consists of a Kalman Filter and a Linear Quadratic Regulator (LQR).The Kalman Filter is used to determine the optimal estimate of the state of the system, and the LQR determines the optimal stimulation needed based on the state estimates to maintain the Epileptor system on a specific trajectory.

These methods have been implemented in a real-time experimental interface (RTXI) platform for animal testing.Seizures will be induced by injection of 4-aminopyridine (convulsant) unilaterally into the hippocampus. Seizureswill be recorded in the hippocampus bilaterally using depth electrodes, and a single stimulation electrode will beplaced in the Ventral Hippocampal Commissure.

Results: Our results show that the LQG method controls seizures in the Epileptor model immediately followingstimulation onset. No seizures escape while the stimulator is on. We also show that the controller was robust tochanges in the Epileptor model parameters during the simulation. This method is able to control seizures even if thesystem dynamics are non-stationary. We are now testing the method in an in vivo rodent model of Epilepsy.

Conclusions: The LQG controller is unique in that it can be designed to be optimal for any system. The systemidentification method determines a subject/patient specific mathematical model of neural dynamics. The model isused to tune the LQR to control seizures while minimizing total stimulation energy. This method is computationallysimple for real-time applications, and could be programmed into an implantable device. References:

1. Morrell MJ, Group RNSSiES. Responsive cortical stimulation for the treatment of medically intractable partial epilepsy.Neurology 2011;77(13):1295

2. Jirsa VK, Stacey WC, Quilichini PP, Ivanov AI, Bernard C. On the nature of seizure dynamics. Brain 2014;137(Pt 8):2210-2230.

Funding: University of Minnesota DTC DTI Seed Grant.

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Accelerating Patient Access to Neuromodulation Therapies: A Practical Tool to Demonstrate Neural Tissue Safety

Authors: Gregory F. Molnar1,2, Dawn Bardot1, Kyle J. Myers3, Bill Murray1, Randall Schiestl4, MDIC Computer Modeling & Simulation Project Team1

Affiliations: 1. Medical Device Innovation Consortium (MDIC), USA; 2. Department of Neurology, University of Minnesota School of Medicine, USA 3. Office of Science & Engineering Laboratories, Center for Devices and

Radiological Health, U.S. Food and Drug Administration, USA; 4. Boston Scientific Corporation, USA.

Background: Neuromodulation devices are used to treat a variety of nervous system disorders and conditions. Despite this wide variety, due to perceived uncertainty in regulatory expectations, each device’s stimulation levels are often limited by a simple combination of parameters: charge per phase and charge density per phase of stimulation. This limit, often known as the “Shannon limit,” was derived from a limited set of experiments conducted over 25 years ago. It is not based on a fundamental understanding of how stimulation over these limits impacts tissue surrounding an implanted electrode nor where the studies related to current commercial modalities of neuromodulation.

Methods: The team conducted a search of the public FDA site of Pre Market Approval Submissions and examined the safety data from current available therapies1. The team also surveyed several industry and FDA stakeholders on their view of the regulatory science in demonstrating neural tissue safety.

Results: It was discovered, though not widely known, that in recent years these traditional theoretical limits of charge density have been tested and largely exceeded in more translational ways. Acute and chronic large animal in vivo experiments using commercial devices and clinical implementations were established to help demonstrate a more realistic quantification of neural tissue impacts from device insertional forces, stimulation effects, and distance from electrode effects. These approaches have led to a more realistic and better clinical risk-benefit understanding.

Conclusions: These findings have lead to new efforts to develop an FDA Medical Device Development Tool2,3, that if approved will allow industry, academic and FDA stakeholders a clear path to test neurostimulation device safety and potentially accelerate patient access to beneficial innovations in this space. References: 1) http://mdic.org/wp-content/uploads/2016/03/Preclinicaldata.xls2) http://www.fda.gov/MedicalDevices/ScienceandResearch/MedicalDeviceDevelopmentToolsMDDT/3) http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm374427.htm

Funding: Medical Device Innovation Consortium

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Sparse Electromagnetic Source Imaging: A Periscope to Guide Neuromodulation TherapiesAbbas Sohrabpour1, Yunfeng Lu1,2, Gregory Worell3, Bin He1,4

1. Department of Biomedical Engineering, University of Minnesota, USA; 2. Medtronic, USA; 3. NeurologyDepartment, Mayo Clinic, USA; 4. Institute for Engineering in Medicine, University of Minnesota, USA

Background: The brain is organized as networks of interconnected neural circuits that each may specialize in specific functions while highly interacting with other nodes of the network [1]. This implies that local perturbations, may demonstrate global effects. Thus, neuromodulation therapies needs to constantly monitor the effects they elicit in the widespread networks of the brain to obtain optimal and desired results. Electromagnetic source imaging (ESI) can provide a means to monitor brain networks in a dynamic fashion, by solving the inverse problem using EEG/MEG recordings. The electrophysiological inverse problem is the process of estimating underlying brain electrical activity from noninvasive surface recordings such as EEG and/or MEG.

Methods: In order to increase the spatial resolution of ESI algorithms, we have incorporated an algorithm within the sparse signal processing framework. We have exploited the fact that brain sources are relatively focal and thus can be represented sparsely (a lot of zeros) when the total variation operator is applied. Based on this idea an iterative reweighting scheme was also proposed to penalize locations where the probability of having sources is minimal, to ultimately separate the active regions from the background without applying any threshold [2]. We tested this proposed new algorithm in focal epilepsy patients who underwent surgery and became seizure-free afterwards (did not respond to medication). The inter-ictal spikes (IIS) were extracted from the pre-operational EEG recordings of these patients and input into the algorithm. The estimated solutions were compared to clinical findings such as surgical resection (obtained from post-operational MRI) and intra-cranial electrodes marked as seizure onset zone (SOZ) by the physician. The estimated solutions needed no thresholding and provided an extended solution for the underlying epileptic sources, thus not only determining the location of epileptic activity but also its extent.

Results: The initial results indicate a good accordance between estimated results and clinical findings. The estimated epileptic sources from non-invasive recordings could estimate the location and extent of epileptic activities quite well, as compared to invasive intra-cranial recordings.

Conclusions: While we validated our proposed ESI algorithm in epilepsy patients, the proposed algorithm could potentially be applied to many other neurological conditions. As EEG provides high temporal resolution solutions, our proposed algorithm can provide a good estimate of the location, extent and dynamics of theunderlying brain networks, which can be extremely useful in a closed-loop neuromodulation setup, where the effects of neuromodulation therapy can be monitored constantly and stimulation parameters adjusted if necessary [3].References:[1]. K. Friston, Brain Connectivity, vol. 1(1), pp. 13-36, 2011. [2]. E. J. Candes et al., Journal of Fourier analysis and applications, vol. 14, pp. 877-905, 2008. [3]. A. G. Rouse et al., Journal of Neural Engineering, vol. 8(3), pp. 036018 (19 pages), 2011.

Funding: NIH EB006433, EY023101, HL117664, NSF CBET-1450956 and CBET-1264782.

Fig. 1. Schematic Diagram of the proposed ESI algorithm and an example of applying the proposed algorithm in analyzing underlying epileptic sources in a right temporal lobe case.

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Title: Temporal Discretization Errors Produce Minimal Effects on Vestibular Prosthesis Performance

Authors: Peter J. Boutros 1,2, Nic Valentin 2, Dale Roberts2, Kristin N. Hageman1, Chenkai Dai MD PhD2,Charles C. Della Santina PhD MD1,2

Affiliations: 1. Johns Hopkins University, Department of Biomedical Engineering, USA; 2. Johns Hopkins University, Department of Otolaryngology – Head & Neck Surgery, USA

Background: Stimulation of surviving vestibular afferent neurons can partially restore the angular vestibulo-ocular reflex (aVOR) in animals and humans with profound bilateral vestibular hypofunction (BVH). A common strategy to encode velocity of head rotations is to stimulate vestibular afferents with biphasic current pulses that are pulse frequency modulated (PFM) according to a smooth head velocity-to-pulse frequency mapping. [1] To translate this technique into a commercially viable treatment for BVH, it would be advantageous to use existing cochlear implant (CI) stimulators. Moreover, if the vestibular implant (VI) portion of a combined VI/CI only requires a subset of thestimulator’s electrodes, then the remaining electrodes could be implanted in the cochlea and used for hearingrestoration. Integrating a PFM-based VI and CI using continuous interleaved sampling (CIS) creates a tradeoff,because temporal discretization inherent to CIS interferes with smooth modulation of pulse frequency. [2] This studyinvestigated the effect of temporal PFM discretization errors on the electrically evoked aVOR.

Methods: One rhesus macaque with BVH due to gentamicin ototoxicity was tested using both a smooth PFM mapping (sPFM) and a mapping corrupted by temporal discretization errors (dPFM) that typify errors that would occur in a VI/CI using CIS. Biphasic current pulses were delivered to individual branches of the left vestibular nerve at varying pulse frequencies to encode virtual sinusoid head motions with peak velocities of 50-400°/s and frequencies of 0.1-5Hz. Responses were assayed using the 3D scleral search coil technique. [3] Stimuli were delivered using a Med El Pulsar CI100 stimulator interfaced with Research Interface Box hardware developed at the University of Innsbruck.

Results: We collected eye movement responses to virtual sinusoids with a peak velocity of 300°/s at frequencies of 0.1, 0.2, 0.5, 1, 2, and 5Hz using both mappings. A three-way ANOVA with mixed interactions showed no significant difference between the gains (F(1,1.04), p=0.308), phase (F(1,1.61), p=0.205), or angle of misalignment from the ideal axis of rotation (F(1,0.1), p=0.747) between the sPFM and dPFM maps across all frequencies and SCCs tested.

Conclusions: Temporal discretization errors in stimuli using the dPFM protocol produced negligible effects on the gain of evoked eye movements. This result shows that approximating pulse-frequency modulation of prosthetic vestibular stimuli may not require temporal resolution more precise than what is available within the constraints of a CI running a CIS stimulation protocol on non-vestibular electrodes. This finding provides solid support for development of VI/CIs using minimally-modified stimulator circuitry.References:[1] Chiang, B., Fridman, G. Y., Dai, C., Rahman, M. a, and Della Santina, C. C., 2011, “Design and performance of a multichannelvestibular prosthesis that restores semicircular canal sensation in rhesus monkey.,” IEEE Trans. Neural Syst. Rehabil. Eng., 19(5), pp.588–98.[2] Wilson, B. S., Finley, C. C., Lawson, D. T., Wolford, R. D., and Zerbi, M., 1993, “Design and evaluation of a continuous interleavedsampling (CIS) processing strategy for multichannel cochlear implants.,” J. Rehabil. Res. Dev., 30(1), pp. 110–6.[3] Migliaccio, A. a, Schubert, M. C., Jiradejvong, P., Lasker, D. M., Clendaniel, R. a, and Minor, L. B., 2004, “The three-dimensionalvestibulo-ocular reflex evoked by high-acceleration rotations in the squirrel monkey.,” Exp. Brain Res., 159(4), pp. 433–46.

Funding: This work was supported by NIH-R01DC9255. PJB amd KNH were supported by NIDCD 2T32DC000023-31 through the Johns Hopkins Center for Hearing & Balance.

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Characterization of cortical SMA-M1 neurophysiological activity in the MPTP nonhuman primate model of Parkinson’s disease during a goal directed reach task.

Authors: Brett A. Campbell1, Claudia M. Hendrix1, Zachary Weinstock2, Yasaman Adibi1, Kenneth Baker1,Jerrold Vitek1

Affiliations: 1. University of Minnesota, Department of Neurology, Center for Neuromodulation Research, USA; 2.University of Minnesota College of Biological Sciences, USA

Background: Parkinson’s disease (PD) is characterized by bradykinesia, rigidity, tremor and a gait disorder. While pathophysiological changes in the basal ganglia thalamo-cortical (BGTC) motor circuit have been reported, the changes in cortical activity and its relationship to motor signs and disease severity is not well understood. This study characterizes task specific changes in the neuro-pathophysiology in SMA and M1 circuitry during goal directed reach in the normal and MPTP NHP. The results providing a physiological biomarker for the development of closed loop deep brain stimulation therapies as well as improving our understanding of the pathophysiological basis underlying the motor deficits observed n PD.

Methods: Healthy and PD state NHPs were trained to perform a visually-cued center-out reach task. Concurrent microelectrode recordings, including paired-SUs within and across M1-SMA cortical sites, were time-locked to task behaviors including reach kinematics and eye movements.

Results: Compared to the normal state, eye movements in the PD state showed i) an increase in the occurrence and duration of eye fixation prior to presentation of the visual go-cue and ii) an increase in time-locked saccades towards the visual target after the go-cue. In contrast, initiation of hand movement after the go-cue was delayed in the PD state compared to the normal state. In addition, the overall coordination of reach kinematics was also impaired resulting in longer reach times, decrease accuracy, and degraded stereotypy in reach paths. Perievent auto and cross-correlograms of SU activity showed a decrease in event related modulation and correlated paired-SU activity in PD.

Conclusions: Saccade initiation towards the target were closely time-locked to the onset of the go-cue and may reflect difficulty in suppressing reflexive saccades towards visual cues. Reach onset, on the other hand, was delayed relative to the onset of the go-cue. Reduced eye latency coupled with prolonged latency in reach initiation would seem paradoxical but could reflect alterations in timing within the motor circuit including premotor cortical areas, regions not recorded from in this study. The task related changes in modulation and increased variability in timing of SMA and MC activity reflect a decrease in time-locked neural modulation leading to degradation in overall visuomotor coordination. This finding is consistent with a model of PD dysfunction that accounts for changes in selective firing patterns, suppression of non-selective firing patterns, and the temporal relationships of neural activity within and across the thalamo-cortical and cortical-cortical motor circuits. Funding: NIH R01 5R01NS077657-04

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Design of a Vestibular Prosthesis for Sensation of Gravitoinertial Acceleration

Kristin N. Hageman1, Margaret R. Chow1, Peter J. Boutros1, Dale Roberts2, Angela Tooker3, Kye Lee3, Sarah Felix3, Satinderpall S. Pannu3, Charles C. Della Santina1,2

1Departments of Biomedical Engineering and 2Otolaryngology - Head & Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD 3Lawrence Livermore National Laboratory, Livermore, CA

Background: The vestibular system of the inner ear contains two classes of motion sensors: three rotational velocity sensors (semicircular canals, SCCs) and two gravitoinertial acceleration (GIA) sensors (utricle and saccule) that encode motion using pulse frequency modulation (PFM) of afferent neuron firing rates. Vestibular sensation of head motion drives ocular, postural and autonomic reflexes that helps maintain steady vision, stable gait and balance. Individuals with profound bilateral vestibular deficiency suffer reduced quality of life. Research toward a vestibular prosthesis has focused on SCC stimulation; however, to more completely restore vestibular reflexes, stimulation of the utricle/saccule is essential [1,2]. The work presented here aimed (1) to design and fabricate electrode arrays suited to chinchilla utricle and saccule and (2) to expand the capabilities of the MVP to encode GIA accelerations.

Methods: We designed electrode arrays for the chinchilla utricle/saccule based on 3D anatomic model from reconstructed micro-CT scans [3]. Thin-film polyimide electrodes were micro-fabricated with multiple layers of trace metal insulated with interleaved layers of polyimide and contacts were designed using electrochemically activated iridium oxide film (101 µm diameter) and tested in 0.9% NaCl saline. In the new MVP system incorporating GIA sensation, a motion processing unit senses angular velocities and linear acceleration. New firmware maps head velocity-to-pulse rate and head acceleration-to-pulse rate. To test this mapping, the motion sensor was mounted onto a 6DOF motion platform. Instantaneous velocity, acceleration, and pulse rates on two electrodes were recorded for analysis.

Results: Micromachining polyimide electrode arrays yields a large number of electrodes while maintaining small size, flexibility, and precisely defined geometry. Based on electrode size, current pulses up to 960 µA at 100 µs/phase can be delivered while maintaining safe charge injection. An average impedance of 12.2 ± 3.1 kOhms at 10 kHz was recorded from ten electrodes on one representative array. The updates to the MVP successfully encode acceleration to PFM pulse trains.

Conclusions: The increased number and organized layout of the electrode contacts in the array provides greater control and increased capabilities for stimulation paradigms, creating the ability to stimulate across the chinchilla utricle and saccule. With the use of the 12 V compliant MVP stimulation circuitry, we can drive the new electrodes up to the safe charge injection limit of 960 µA/phase. With the results from the additions to the MVP architecture, we will be able to deliver PFM stimulation for the utricle/saccule to encode GIA.

References:[1] Fridman, G. Y., and Della Santina, C. C., 2012, “Progress Toward Development of a Multichannel Vestibular Prosthesis for Treatment

of Bilateral Vestibular Deficiency,” Anat. Rec. Adv. Integr. Anat. Evol. Biol., 295(11), pp. 2010–29.[2] Della Santina, C. C., Migliaccio, A., and Patel, A. H., 2007, “A multichannel semicircular canal neural prosthesis using electrical

stimulation to restore 3-D vestibular sensation.,” IEEE Trans.Biomed.Eng, 54(6 Pt 1), pp. 1016–30.[3] Hayden, R., Sawyer, S., Frey, E., Mori, S., Migliaccio, A. a, and Della Santina, C. C., 2011, “Virtual labyrinth model of vestibular

afferent excitation via implanted electrodes: validation and application to design of a multichannel vestibular prosthesis.,” Exp. BrainRes., 210, pp. 623–40.

Funding: This work was supported by NIDCD R01DC009255. KNH and PBJ were supported by NIDCD2T32DC000023-31 through the Johns Hopkins Center for Hearing and Balance. Polyimide microelectrode arrays were designed and fabricated with funding from NIDCD contract Y1-DC-8002-01 and under the auspices of the U.S. Department of Energy by the Lawrence Livermore National Laboratory, Contract number DE-AC52-07NA27344.

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Deciphering Generalized Epileptic Networks with Multimodal NeuroimagingZhiyi Sha1, Clara H. Zhang2, Abbas Sohrabpour2, Thomas Henry1, Bin He2,3

1. Department of Neurology, University of Minnesota, USA; 2. Department of Biomedical Engineering, Universityof Minnesota, USA; 3. Institute for Engineering in Medicine, University of Minnesota, USA

Background: Idiopathic generalized epilepsy (IGE) has wide range effects over the whole brain, affecting many networks. The underlying mechanisms of IGE are not well understood (compared to focal epilepsy) and need further studying. Neurostimulation therapy would be an ideal treatment for IGE patients not responding to anticonvulsant medication, only if the underlying network mechanism is well comprehended [1]. We employed multimodal (EEG/fMRI) neuroimaging techniques to determine a potential target node. The thalamocortical connections were proven to be heavily involved in the generation and propagation of generalized spike-and-wave discharges (GSWDs); furthermore we observed that the mediodorsal nuclei (MDN) of the thalamus played a key role in triggering cortical activation of GSWDs, thus being a potential target for neurostimulation therapies [2].

Methods: 10 patients clinically diagnosed with IGE, and 10 healthy controls were recruited in this study. IGE patients had clear inter-ictal GSWDs in their EEG recordings and had normal brain MRI. 64-channel EEG was recorded during resting state fMRI sessions. Later, EEG-informed fMRI analysis was performed to identify network nodes related to GSWD activation. To further, validate this step, seeds were placed in regions of interest (ROI) determined by the EEG-fMRI analysis or EEG source imaging results. Furthermore, group seed-based ROI connectivity analysis of the healthy control and IGE patients revealed that the specific thalamocortical network, including the MDN and the medial frontal cortex, was only observed in IGE patients and not controls. Additional control seeds were also tested in the patient group and no other nodes were found (involved with GSWDs). After the nodes were determined, EEG source imaging was performed and Granger causality analysis was completed on the time series of the determined nodes (MD and ACC) to investigate the dynamics of therevealed thalamocortical network. A one second window around the GSWDs was chosen for this analysis.

Results: The EEG-informed fMRI analysis revealed a strong involvement of the MDN of thalamus and the anterior cingulate cortex (ACC), with the GSWD activity. Seed-based ROI analysis in healthy controls did not show this connection, thus further validating its role in the generations and propagation of GSWDs. Furthermore, the Granger causality analysis revealed that the information flow between the thalamus and ACC was unbalanced and much more driven by the thalamus [2].

Conclusions: Multimodal neuroimaging provides a high spatio-temporal resolution framework to study dynamic networks, more accurately [3]. Our current study investigated the IGE network, and through systematic and objective measures determined a potential target for neuromodulation therapy. References:[1]. R. Fisher et al., Epilepsia, vol. 51(5), pp. 899-908, 2010. [2]. C. H. Zhang et al., NeuroImage Clinical, vol. 9, pp. 117-127, 2015.[3]. B. He et al., IEEE Transaction on Biomedical Engineering, vol. 58(7), pp. 1918-1931, 2011.

Funding: NIH EB006433 and NSF CBET-1450956, CBET-1264782.

Fig. 1. Summary of the Multimodal neuroimaging results in seed based ROI fMRI analysis, EEG-informed analysis and the Granger Causality Analysis.

96


Title: Optogenetic self-stimulation of the infralimbic-accumbens pathway: Opposing effects of abstinence from repeated cocaine and cocaine re-exposure.

Authors: A. Asp1, E. B. Larson1, M. Esguerra1, M. C. Hearing1, K. A. Silvis1, C. Zhang1, M. J. Thomas1;

Affiliations: 1. Neurosci., Univ. of Minnesota, Minneapolis, MN

Background: Mice will actively self-administer optogenetic stimulation of glutamatergic inputs to the nucleus accumbens shell (NAcSh) (Stuber et al. 2012; Britt et al. 2012). In drug-naïve animals, optogenetic self-stimulation is largely input-pathway independent, suggesting that glutamate non-discriminately supports behavioral reinforcement (Britt et al. 2012). However, it is unknown how cocaine experience may alter the ability of glutamatergic inputs to the nucleus accumbens shell to promote behavioral reinforcement. We have previously shown that abstinence from repeated cocaine and cocaine re-exposure produce bidirectional synaptic plasticity in the nucleus accumbens shell. Furthermore, while input-specific changes in glutamatergic synaptic function are apparent during cocaine abstinence (Pascoli et al. 2012), the effects of cocaine re-exposure inabstinence on input-specific plasticity is unknown. Therefore, to better understand how input-specific plasticityinduced by cocaine experience may alter the ability of excitatory transmission in the NAcSh to reinforce behavior, we compared input-specific optogenetic self-stimulation behavior in animals with different histories ofcocaine experience.

Methods: C57Bl/6J mice were infected with channelrhodopsin in either the infralimbic cortex (IL), ventral hippocampus (vHipp), or basolateral amygdala (BLA), and optical fibers were implanted over the NAcSh to allow for selective stimulation of these inputs. Mice were next treated with saline or a cocaine sensitizationregimen (15 mg/kg i.p, 5 once daily injections) followed by 10-14 days of abstinence. A spatial optical self-stimulation task was used to assess behavioral reinforcement after cocaine abstinence, or after being re-exposed to cocaine in abstinence. Whole cell patch clamp electrophysiolgy recordings were taken in nucleus accumbens shell medium spiny neurons to determine if cocaine exposure alters optogenetically-evoked excitatory postsynaptic currents of specific inputs into the nucleus accumbens.

Results: We found that IL-NAcSh self-stimulation was more pronounced in cocaine-abstinent mice comparedto drug-naïve controls (10 hz, 5 ms, 5 s max pulse per entry into the “active” zone). Interestingly, cocaine re-exposure dampened IL-NAcSh self-stimulation behavior to levels of control mice. In contrast, self-stimulationof vHipp-NAcSh inputs was enhanced by cocaine abstinence, and further augmented by cocaine re-exposure. Importantly, these different behavioral effects were paralleled by input-specific changes in synaptic plasticity asmeasured by whole cell patch clamp recordings in medium spiny neurons.

Conclusions: Together, our findings suggest that input-specific changes in plasticity with cocaine abstinence and re-exposure directly modify the reinforcing effects of glutamate in the NAcSh.

References:

Stuber GD, Sparta DR, Stamatakis AM, van Leeuwen WA, Hardjoprajitno JE, Cho S, Tye KM, Kempadoo KA, Zhang F, Deisseroth K, Bonci A (2011) Excitatory transmission from the amygdala to nucleus accumbens facilitates reward seeking. Nature 475: 377-380.

Britt JP, Banaliouad F, McDevitt RA, Stuber GD, Wise RA, Bonci A (2012) Synaptic and behavioral profile of multiple glutamatergic inputs to the nucleus accumbens. Neuron 76: 790-803.

Pascoli V, Turiault M, Luscher C (2012) Reversal of cocaine-evoked synaptic potentiation resets drug-inducedadaptive behavior. Nature 481:71-75.

Funding: R01 DA019666, K02 DA035459, University of Minnesota MnDrive, Breyer-Longden Family Research Fund

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Title: Controlling Plasticity in Sensory Cortical Regions Using Multisensory Neuromodulation Authors: Cory D. Gloeckner1, Jio C. Nocon1, Hubert H. Lim1

Affiliations: 1. University of Minnesota, United States, Biomedical Engineering Department

Background: Sensory systems are vastly connected in the brain through multisensory integration, allowing us to observe the environment around us as one “perception” instead of separate sensory viewpoints. Previous studies have shown that one sensory system can alter neural firing in another [1,2]. The ability to modulate spike activity using noninvasive and controlled sensory stimulation that takes advantage of existing multimodal pathways may potentially treat various neural sensory disorders. In this study, we investigated changes in sensory cortical activity induced by paired stimulation of two different sensory systems with specific temporal delays. We recorded spike activity in olfactory piriform cortex (OC), gustatory cortex (GC), primary somatosensory cortex (S1), and primary auditory cortex (A1) of guinea pigs.

Methods: We positioned 32-site electrode arrays in the right A1, S1, OC, and GC of ketamine-anesthetized guinea pigs and recorded sensory receptor-driven spike activity. For each cortical area, the stimulation of its corresponding sensory system receptors was paired with the receptor stimulation of another sensory system, and the spontaneous and receptor-driven spike activity before and after stimulation were compared to assess modulatory/plasticity effects. Subcutaneous needle electrodes were used to electrically stimulate the skin of various body regions for somatosensory activation. Surface electrodes stimulated the tongue and inner nostrils for gustatory and olfactory activation respectively. Broadband noise was played into the left ear as auditory stimulation. All cortices were located using known stereotactic coordinates [3] and functional responses to receptor activation.

Results: We observed different effects depending on sensory stimulation pairings and recording location. For example, combining somatosensory stimulation with auditory stimulation either suppressed or facilitated neural firing in A1 depending on the inter-stimulus delay, while this combination caused strictly suppressive effects in S1 regardless of delay. OC and GC showed no excitatory responses to somatosensory stimulation alone, but were suppressed or facilitated if combined with gustatory or olfactory stimulation. Also, auditory stimulation had stronger modulatory effects for the lower body areas than upper body areas of the homunculus in S1.

Conclusions: By taking advantage of existing multisensory integration circuitry, we can induce changes in neural firing in different sensory cortices. By optimizing stimulation parameters, such as stimulation location and inter-stimulus delay, we can potentially treat neural sensory disorders (e.g. tinnitus, chronic pain) by altering the abnormal spike patterns driving those disorders. Future studies should investigate the use of other non-sensory multimodal pathways, such as motor and cognitive circuits, for the potential treatment of other neurological and psychiatric disorders. References:

[1] Craig D. Markovitz, Benjamin T. Smith, Cory D. Gloeckner, Hubert H. Lim. “Investigating a new neuromodulation treatment forbrain disorders using synchronized activation of multimodal pathways.” Scientific Reports 5:9462, 2015.

[2] Gregory J. Basura, Seth D. Koehler, Susan E. Shore. “Multi-sensory integration in brainstem and auditory cortex.” Brain Research1485:95-107, 2012.

[3] Gerardo Biella, Marco de Curtis. “Olfactory Inputs Activate the Medial Entorhinal Cortex Via the Hippocampus.” Journal ofNeurophysiology 83:4 1924-1931, 2000.

Funding: NSF IGERT DGE-1069104, MD5M Lions Hearing Foundation, NIH NCATS UL1 TR000114 and MnDRIVE Innovations Grant

98


Title: 180-Day, in vivo Study of Electrodeposited PtIr Electrodes for Neuromodulation

Authors: Artin Petrossians1, John J. Whalen III1,2, James D. Weiland1,2

1. Department of Ophthalmology. University of Southern California. Los Angeles, CA2. USC Institute for Biomedical Therapeutics. University of Southern California. Los Angeles, CA

BackgroundNeuromodulation devices are used for treatment of conditions ranging from Parkinson’ and epilepsy to deafness and blindness, to depression and chronic back pain. These devices function by transferringelectrical stimulation pulses to targeted tissues through electrodes, and research continues to exploredecreasing the size of these electrodes to increase the number of interfaces for more precise targeting oftherapies and integration of closed feedback systems. State-of-the-art electrode materials are approachingtheir charge density limits, thus limiting further size reduction; therefore developing new, reliable and efficient material interfaces is a major challenge for enabling next generation neuromodulation therapies. Recently, a process for electrodepositing low-impedance coatings of platinum-iridium (PtIr)with significantly greater charge density limits was developed and validated in vitro. In this study, deep brain stimulation (DBS)-style microelectrodes modified with this PtIr coating were chronically implanted in rabbit cortex to assess electrochemical performance and tissue response over 180-days ofimplantation vs. conventional platinum electrodes.

MethodsSix rabbits were unilaterally implanted in the cerebral cortex with a 4-contact, DBS-style electrode lead (Ad-Tech) for 30 days (n=2), 90 days (n=2) or 180 days (n=2). Contacts on each lead were randomly assigned (3:1) to either the 60-40 PtIr alloy group or the control group (no coating). All electrode contacts were electrochemically characterized in-situ [electrochemical impedance spectroscopy (EIS), biphasic pulsetesting and cyclic voltammetry (CV)] at implantation and at study endpoint. Impedance, charge injectionproperties and local tissue responses were characterized at each endpoint and compared to baseline.

ResultsElectrochemical impedance of PtIr-coated implants at baseline showed up to a 10x reduction in magnitude (|Z|) at baseline vs. the conventional Pt electrodes (control) in the 100 to 1,000 kHz frequency ranges. PtIr-coated electrodes maintained over 10x lower |Z| vs. control for up to 180 days. Biphasic pulse data showed a similar trend. Encapsulation layer thickness at PtIr coated microelectrodes showed no significant difference compared to the control electrode material.

ConclusionsElectrodeposited PtIr coatings show sustained improvement in electrochemical performance following 180-days implantation in cerebral cortex vs. conventional platinum electrodes. PtIr induces nosignificant difference in surrounding cerebral cortex tissues vs. conventional platinum electrodesfollowing 180-days implantation.

References.

Funding.This project was supported by the USC Wallace Coulter Translational Partnership.

Presenting author email: [email protected]

Presenting author is faculty.

99


Deep brain stimulation using rotating and spatially selective E-fieldsLauri J. Lehto1, Lynn Utecht1, Matthew Johnson2, Olli Grohn3, and Shalom Michaeli1

1. CMRR, University of Minnesota, USA; 2. Department of Biomedical Engineering, University of Minnesota, USA;3. University of Eastern Finland, Finland

Background: Deep brain stimulation uses electric fields that are usually not directionally controlled, yet the direction of the axons to be excited likely has a vital role since their excitability is related to the potential field change along the axonal body [1]. The overall goal of this project is to yield more energy efficient and spatially selective strategies for neuromodulation using DBS. The main objective of our study is to evaluate novel DBS paradigms which are based on amplitude and frequency modulated waveforms for generating spatially selective and rotating fields using multichannel electrodes. We hypothesize that this approach will be more efficient in stimulating ensemble of axons with different orientations, and on the other hand it will enable flexibility to seek an optimal directionality of stimulation with the subsequent stimulation in that direction only.

Methods: As a proof of concept we are currently exploring tripolar electrodes, as three channels in an electrode is the minimum requirement to achieve a rotating E-field. Each channel is independently driven by separate stimulus isolators that are further controlled by a digital-to-analogue converter. The output of each channel is a sinusoid with 2/3π phase differences leading to a rotation of the E-field below the tip of the electrode. The electrodes are implanted into the rat brain and the responses to stimulation are detected using simultaneous functional magnetic resonance imaging (fMRI) at the 9.4 T animal system.

To verify the functionality of our setup, we have driven the three channels of the electrode in unison as a monopolar electrode (120 µs pulse length, 20 Hz, 1-2 mA) using biphasic rectangular pulses. The electrode was implanted into the ventral posteromedial thalamic nucleus.

Results: Our preliminary studies indicate that robust activations in primary somatosensory cortex (4-5 % signal response from baseline) are detected using monopolar, bipolar and multichannel rotating field electrodes. To test spatially selective and rotating E-field paradigms of stimulation, we plan to implant the electrode into the corpus callosum and hippocampal area CA3 where the fiber orientations are well defined. These studies are currently underway in our laboratory.

Simulations using COMSOL clearly demonstrate rotation of the E-field and the possibility to generate its directionality. The simulations also show that the smoothness of the rotation considerably improves when the number of channels increases. We plan to extend our modelling using NEURON software to better investigate the behavior of axons in a rotating E-field.

Conclusions: Our experimental set up on rat animal models generates a framework for studying novel stimulation paradigms for DBS using spatially selective and rotating fields. References:

[1] Rattay, Neuroscience, 1999.

Funding: MnDRIVE.

100


Title: Low frequency desynchronization in the Supplementary Motor Area (SMA) of healthy and parkinsonian nonhuman primates (NHPs).

Authors: Yasaman Adibi1, Claudia Hendrix1, Brett Campbell1, Kenneth Baker1, Jerrold L. Vitek1

Affiliations: 1. University of Minnesota, Department of Neurology, Center for Neuromodulation Research

Background: Parkinson’s disease (PD) is a movement disorder characterized by rigidity, bradykinesia, tremor and a gait disorder. Although a network disorder affecting subcortical and cortical structures, little is understood concerning the changes in neural activity in the Supplementary Motor Area (SMA). Recording local field potentials (LFPs) from these areas in the healthy and Parkinsonian nonhuman primate model, provides a means to characterize the low frequency oscillatory changes postulated to underlie the development of motor signs associated with PD. It is hypothesized that low frequency oscillations (0-12Hz and 13-30 Hz), related to LFPs in SMA in the Parkinsonian state are greater than the normal condition.

MethodsTo characterize changes in signal processing in PD, spectrograms of LFPs in the SMA during epochs of a controlled 8-choice center-out reaching task, were studied. Since a large degree of energy in a signal is in lower frequencies (below 200Hz), direct application of short window frequency time (SWFT) analyses onLFPs at high rate (24 kHz) is time and computationally intensive. A band-width selective SWFT analysis has been developed that allows one to focus on low frequency activity despite the resolution limitation dictated by the sampling rate and window size of the data. The spectrograms of each recording session are conditionally averaged over differential trials that are temporally aligned on the same epoch events.

ResultsThe aforementioned method was applied to several datasets from two monkeys in the normal and PD state. Conditional averaging was performed over at least 80 trials in each recording session. Preliminary results reveal that changes occur in desynchronization of alpha and beta frequency activity. In healthy state, a peak in low frequency band between 0 and 10Hz occurs, immediately after visual cue and remains elevated until the return to start pad. In the Parkinsonian state, while alpha increases after visual cue, its overall strength is lower over trial. In contrast, in both healthy and PD monkeys a decrease is observed in beta (13Hz to 30Hz) power, after the go cue.

Conclusions This study demonstrates the importance of task-balanced analysis of pathophysiological activity in SMA in differentiating healthy from Parkinsonian state. This approach may be useful in defining not only the development and progression of PD, but may also be used as biomarker for closed loop DBS systems that are task, time and phenotype specific.

FundingNIH R01 5R01NS077657-04

101

Minnesota Neuromodulation Symposium, April 2016MNS 196

Cortical implantation of a 16-channel wireless floating microelectrode array (WFMA) stimulator Philip R. Troyk1,2,3, David Frim2, Ben Roitberg2, V. Leo Towle2, Sungjae Suh1, Martin Bak4, Zhe Hu3

1.Illinois Institute of Technology, USA; 2.University of Chicago, USA; 3.Sigenics, Inc, USA; 4.Microprobes for Life Science, USA

Background: The 16-channel WFMA stimulator is a miniature wireless implantable stimulator (5mm diameter x 0.5 mm thickness) designed for use in the visual cortex for an intracortical visual prosthesis, and has been previously described for peripheral implantations within rodents [1,2]. Presently, these peripheral implanted WFMAs remain functional after 16 months with experimentation on-going. This novel stimulator has numerous potential uses for cortical prostheses, and cortical neuromodulation within motor and sensory cortex. Here, we describe the first use for cortical implantation in Macaque. Two animals each received two WFMAs implanted in motor cortex in order to test the feasibility of the surgical procedure and demonstrate their chronic functionality.

Methods: WFMAs were fabricated by Microprobe for Life Science and Illinois Institute of Technology. Each WFMA contains 16 AIROF electrodes combined with wireless electronics that allows for powering and communication over a transcutaneous inductive link operating at 5MHz. Following an approved animal protocol at the University of Chicago, a craniotomy was made over the central sulcus and a hand-held stimulation probe was used to identify motor areas for the hand and face.The WFMAs were placed into these cortical areas using a custom high-speed motorized insertion tool that propels the devices into the cortex at 1m/sec [3]. The dura was closed and the skull bone fragment replaced using titanium straps.

Results: The WFMAs were successfully implanted as assessed by visual observation of no surface blood vessel leakage and stable post-insertion positioning. Electrical operation of the WFMAs was confirmed by verifying communication with the implanted devices immediately following surgery. Initial testing of the first animal, one week post implant, showed continued electrical operation and visual evidence of hand and face movements caused by the wireless commanding of the WFMAs. Due to anesthesia time limits in this first testing session, more extensive testing in the awake animal is scheduled. Initial and chronic testing in the second animal arealso imminent.

Conclusions: While at the time of this writing the results are preliminary, based upon the longevity of the WFMAs in the rodent experiments, it is expected that upcoming chronic testing in the Macaque will similarly show extended and comprehensive functionality. These first-ever demonstrations of cortical implantation are significant in that a fully implantable 16-channel intracortical stimulator requiring no percutaneous connection has numerous uses for neural modulation within motor and sensory cortex and may enable neural prostheses for vision or hearing, pain control using sub-motor stimulation and epilepsy control via a hand held transcutaneous control unit, and stimulation for neuroscience research. Peripheral applications may include intraspinal stimulation for restoration of standing/walking, and emerging bioelectronic medicine applications.References:1. Troyk, P, Bredeson, S, Cogan, S, Romero-Ortega, M, Suh, S, Hu, Z, Kanneganti, A, Granja-Vazquez, R, Seifert, J

& Bak, M 2015, 'In-vivo tests of a 16-channel implantable wireless neural stimulator'. in InternationalIEEE/EMBS Conference on Neural Engineering, NER. vol. 2015-July, 7, IEEE Computer Society, pp. 474-477,7th International IEEE/EMBS Conference on Neural Engineering, NER 2015, Montpellier, France, 22-24 April.,

2. S. Bredeson, A. Kanneganti, F. Deku, S. Cogan, M. Romero-Ortega and P. Troyk, "Chronic in-vivo testing of a16-channel implantable wireless neural stimulator," Engineering in Medicine and Biology Society (EMBC), 201537th Annual International Conference of the IEEE, Milan, 2015, pp. 1017-1020.

3. S. D. Bredeson and P. R. Troyk, "Device for the implantation of neural electrode arrays," Engineering in Medicineand Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, Chicago, IL, 2014, pp.434-437.

Funding: Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Material Command, Contract W81XWH-12-1-0394; Gifts to IIT; Sigenics internal R &D.

102


Phasic Burst Stimulation: A Novel Approach for Optimizing Closed-Loop Deep BrainStimulation

Authors: Abbey B. Holt, Max Shinn, Theoden I. Netoff Affiliations: 1. University of Minnesota, USA

Background: High frequency deep brain stimulation (DBS) is effective at treating motor symptoms of Parkinson’s disease (PD). With the development of electrodes that can sense the neural signal, there is a push to develop closed-loop approaches to parameter setting. Oscillatory activity in the beta frequency range (12-35 Hz) provides a potentialbiomarker for closed-loop stimulation, as therapeutic DBS has been shown to disrupt this activity1. Here we propose a novel approach to optimally suppress pathological oscillations based on patient physiology. While stimulationtriggered off the phase of an oscillation has been proposed to suppress pathological beta oscillations, we hypothesizethat providing a burst of stimulus pulses over a range of phases, termed Phasic Burst Stimulation (PhaBS), will moreefficiently and effectively desynchronize the activity. Furthermore, we propose the optimal phase range can bepredicted using subject-specific physiological responses to stimulation.

Methods: A simple measure called a phase response curve (PRC), which describes how the phase of an oscillationchanges depending on the stimulus phase, is used to predict how PhaBS modulates oscillatory activity. Using pulsecoupled oscillatory theory, we can predict the effects of periodic stimulation on a network of neurons. When the slope of the PRC is greater than one, stimulation will desynchronize neurons, but when the slope is less than one,stimulation will synchronize neurons. PRC-optimized PhaBS was tested in: 1) acomputational model with an emergentparkinsonian oscillation2 and 2) singlepatch-clamped neurons in the substantianigra pars recitulata which were entrained toan externally applied oscillation.

Results: First, we show PhaBS more effectively modulates a pathological oscillation in a computational model of the basal ganglia than applying a single stimulus pulse per cycle. Furthermore, from the measured PRC we are able to predict both an optimal stimulus phase as well as burst frequency. Next, we provide proof-of-concept evidence in vitro by demonstratingthe PRC can be used to predict the effects of PhaBS on entrainment of a neuron to anoscillatory input.

Conclusions: Overall we provide support for a novel PRC-optimized approach to closed-loop DBS. Closed-loop algorithms have many advantages over solely physician tuned approaches as they have the potential to: 1) improve efficacy; 2) reduce negative side effects withdecreased stimulation amplitude 3) achieve optimal stimulus settings in less time 4) enhance battery life; and 5) stabilize fluctuations in motor symptoms. References:1. Brown, P., Abnormal oscillatory synchronisation in the motor system leads to impaired movement. Current opinion in neurobiology2007, 17 (6), 656-664.2. Hahn, P. J.; McIntyre, C. C., Modeling shifts in the rate and pattern of subthalamopallidal network activity during deep brainstimulation. Journal of computational neuroscience 2010, 28 (3), 425-441.

Funding: MnDrive Neuromodulation Fellowship, NSF-UMN Neuroengineering IGERT.

Figure 1. PRCs can be used to predict optimal stimulation parameters to modulate synchrony. Left: PhaBS was applied in single cells. Predictions from the PRC (black) match well with experimental results (red). Right: The PRC could be used to predict the effects of PhaBS in a computational model of Parkinson’s disease. Also, PhaBS was more effective than a single stimulus pulse per cycle.

103


Cerebellar tDCS interferes with cortical excitability during a motor training task Rebekah Summers1, Mo Chen2, Cecilia N. Prudente1, Teresa J. Kimberley1

1. University of Minnesota, Department of Physical Medicine and Rehabilitation, Programs in Physical Therapy andRehabilitation Science; 2. University of Minnesota, Institute for Engineering in Medicine

Background: Cerebellar activity can be modulated using transcranial direct current stimulation (tDCS) and when applied concurrently with a motor task has been shown to facilitate learning in healthy persons. The aim of this work was to determine if visual-spatial motor learning and neurophysiologic measures are affected by cerebellar tDCS when delivered during a finger tracking task.

Methods: A two group (real vs sham), double blind design was implemented. 15 healthy adults (7 female, age 28.8±10.5 years) completed one session of finger tracking with simultaneous anodal or sham cerebellar tDCS. Cerebellar tDCS was delivered using a constant current of 2mA. Anode: between the level of the mastoid process and inion, along the midline of the head. Cathode: buccinators muscles ipsilateral to the training hand. The tracking task involved index finger flexion and extension using a potentiometer to control the height of a constantly moving cursor that was displayed on a screen before the subject. Training and accuracy testing included unique waveform parameters. Tracking training with simultaneous cerebellar tDCS was completed in two 15 min epochs with a 5 min break (total 30min stimulation). Tracking accuracy and cortical excitability was measured immediately before and after the training period. Motor cortex excitability was determined using transcranial magnetic stimulation single pulse peak to peak amplitude of the motor evoked potential (MEP) and cortical silent period (CSP) in the first dorsal interosseous.

Results: Tracking accuracy was significantly increased within both groups at posttest (p < 0.001); however tracking accuracy change scores were not different between groups (p =0.144). MEP amplitude change scores were significantly different between groups (p = 0.014). Single pulse MEP was increased in the sham group (p < 0.0001), indicating increased excitability from baseline while the anodal group displayed a decrease in excitability (p = 0.003). There were no between group differences for CSP (p = 0.275), yet within group CSP duration was significantly prolonged, suggesting increased in inhibition in the anodal group (p < 0.001) while unaffected in the sham group (p = 0.065).

Conclusions: Neurophysiologic measures of brain excitability indicate that anodal tDCS interferes with the normal increase in cortical excitability following a motor training activity. However, there is no clear advantage of anodal tDCS compared to sham during training to improve visual-spatial tracking accuracy. These results suggest that cerebellar tDCS has an influence on brain excitability in locations distant from the active electrode when combined with a motor task. References:None.

Funding: Institute for Engineering in Medicine Pilot Project Funds

104


A Miniaturized Brain-Machine-Spinal Cord Interface (BMSI) for Closed-Loop Intraspinal Microstimulation

Shahab Shahdoost1, Shawn Frost2, David Guggenmos2, Caleb Dunham2, Jordan Borrell2, Scott Barbay2, Vanessa Tolosa3, Randolph Nudo2, Pedram Mohseni1

1. Case Western Reserve University, USA; 2. University of Kansas Medical Center, USA; 3. LawrenceLivermore National Laboratory, USA

Background: The main objective of this work is to develop and employ a miniaturized brain-machine-spinal cord interface (BMSI) for enhancing functional recovery after spinal cord injury (SCI) [1]-[3]. We hypothesize that artificial synchronous activation of the spared corticospinal connections via intraspinal microstimulation (ISMS) triggered by neural spike activity in the hindlimb motor cortex will encourage synaptic facilitation and result in improved control of movement in a rat model of SCI. This work combines neurobiological tools with next-generation microdevice technology to explore whether closed-loop neuromodulation approaches can be used to strengthen synapses in the spinal cord and enhance motor recovery after SCI.

Methods: A battery-powered, wireless microdevice records and discriminates in real-time neural action potentials (spikes) in the hindlimb motor cortex and delivers ISMS below the level of a lower-thoracic contusion injury in a rat model of SCI. Specifically, an integrated circuit (IC) that lies at the core of the BMSI microdevice performs multichannel amplification and 10b digitization of the extracellular neural spikes recorded by a multisite electrode array placed in the hindlimb motor cortex. The IC subsequently identifies the presence of neural spikes in the recorded data on each channel based on thresholding and user-adjustable time-amplitude windowing to trigger multichannel ISMS and deliver precisely controlled stimulus current pulses of ≤ 100µA via a second multisite electrode array placed in the spinal cord.

Results: Acute neurophysiological experiments were performed in healthy laboratory rats, as well as in rats that had received a contusion injury to the thoracic spinal cord at level T8-T9 several weeks prior to the experimental sessions. The miniaturized BMSI was capable of converting in real-time the neural command signals recorded from the cerebral cortex to electrical stimuli delivered to the spinal cord below the injury level. For proof-of-concept of closed-loop, real-time, cortical control of ISMS in an anesthetized rat, distinct muscle pattern activation was demonstrated via ISMS-evoked, fine-wire EMG signals recorded from multiple hindlimb muscles of the rat. In another set of experiments, EMG signals were also recorded from hindlimb muscles in response to open-loop ISMS in the lumbar enlargement of an anesthetized SCI rat using a multisite, flexible, polymeric microelectrode array.

Conclusions: This work demonstrated proof-of-concept of a fully miniaturized BMSI that can convert in real-time intracortical neural spikes into electrical stimuli delivered to the spinal cord below the level of the injury, which is envisioned to facilitate functional recovery after SCI by conditioning long-range corticospinal connections spared after the injury. References: [1] S. Shahdoost, S. Frost, C. Dunham, S. DeJong, S. Barbay, R. Nudo, and P. Mohseni, “Cortical control

of intraspinal microstimulation: Toward a new approach for restoration of function after spinal cordinjury,” in Proc. 37th Annu. Int. IEEE Eng. Med. Biol. Conf. (EMBC’15), pp. 2159-2162, Milan, Italy,August 25-29, 2015.

[2] J. B. Zimmermann and A. Jackson, “Closed-loop control of spinal cord stimulation to restore handfunction after paralysis,” Front. Neurosci., vol. 8, no. 87, pp. 1-8, May 2014.

[3] Y. Nishimura, S. I. Perlmutter, and E. E. Fetz, “Restoration of upper limb movement via artificialcorticospinal and musculospinal connections in a monkey with spinal cord injury,” Front. NeuralCirc., vol. 7, no. 57, pp. 1-9, April 2013.

Funding: A generous gift from the Ronald D. Deffenbaugh Foundation

105


In-vitro Examination of Epileptic Seizure Suppression Mechanism by Electrical StimulationSora Ahn1, Sumin Jo1, Hyang Woon Lee1, Sang Beom Jun1, Seungjun Lee1

1. Ewha Womans University, Korea

Background: Recently, epileptic seizure suppression by deep brain stimulation (DBS) is receiving attention as a new treatment of refractory epilepsy. However, the suppression mechanism by electrical stimulation is still unclear so that it is difficult to improve efficacy of the method. In this paper, we examined the suppression effect by electrical stimulation with two different experimental models to figure out the mechanism underneath.

Methods:We carry out in-vitro experiment by using hippocampal-entorhinal cortex (EC) combined slices of rat. Seizure-like events (SLEs) are induced by two different drugs, 4-aminopyridine (4-AP) and bicuculline (BCC). Local field potentials are recorded by a micro-electrode array (MEA) which enables simultaneous monitoring of whole hippocampal area including EC. After 2-3s from a spontaneous SLE, we applied high frequency stimulation (130Hz, 500uA, 1ms pulse-width, biphasic, cathodic first) to EC which is significant neural pathway connecting hippocampus and neocortex.

Results:In BCC bath application, SLEs in EC (or some part of EC) are suppressed immediately after stimulation whereas SLEs in other regions remained. This indicates that electrical stimulation can suppress SLEs locally near stimulating zone but not globally. Meanwhile, in 4-AP bath application, the suppression effect was not clearly seen, not even locally. That is because 4-AP, the potassium channel blocker, interferes potassium efflux during stimulation. The results imply that neuronal depolarization blocking through accumulation of extracellular potassium ion is an important factor for seizure suppression.

Fig. 1 Suppression Effect of SLEs in BCC (left) and 4-AP (right)

Conclusions:Our experimental results support ‘potassium accumulation hypothesis’ which is one of the generally accepted theories to understand seizure suppress phenomena due to electrical stimulation [1, 2]. The results also mean that different stimulation strategies are required according to etiology of seizure generation. References:[1] Fertziger, A. P. and J. B. Ranck: Potassium accumulation in interstitial space during epileptiform seizures. Experimental neurology1970, 26(3): 571-585.[2] Fröhlich, F., M. Bazhenov, V. Iragui-Madoz and T. J. Sejnowski: Potassium dynamics in the epileptic cortex: new insights on an oldtopic. The Neuroscientist 2008, 14(5): 422-433.

106


Differential Effects of Noisy and Sinusoidal Galvanic Vestibular Stimulation on Resting-State Functional Connectivity

Soojin Lee1,4, Jiayue Cai2, Diana J. Kim3, Z. Jane Wang2, Martin J. McKeown3,4

1. Department of Biomedical Engineering, University of British Columbia, Canada; 2. Department of Electrical andComputer Engineering, University of British Columbia, Canada; 3. Department of Medicine, University of British

Columbia, Canada; 4. Pacific Parkinson’s Research Centre, University of British Columbia, Canada

Background: Parkinson’s disease (PD) is characterized by motor symptoms including tremor, rigidity, bradykinesia, and often cognitive impairments. As pharmacological (and surgical) treatments have limitations, alternative therapeutic methods such as non-invasive brain stimulation are being actively pursued. Preliminary studies have suggested that Galvanic Vestibular Stimulation (GVS) may be a useful adjunctive therapy [1], but its mechanisms are unknown; it may modulate ongoing brain rhythms or stimulate underactive brain regions in PD. Moreover, the optimum type of stimulus is unclear. Here we investigated the effects of different stimuli on functional connectivity in PD and controls using fMRI.

Methods: A total of 15 mild-moderately affected PD subjects (3 female; mean age: 65.7±8.8 years; 1 left-handed; off medication) and 6 age-matched healthy controls (HC) (2 females; mean age: 57.0±9.7 years; all right-handed) participated in the study. We applied either noisy (nGVS: 0.1–10 Hz; 1/f-type power spectrum; 90% of individual threshold) or sinusoidal (sGVS: 1 Hz; 500 µA) stimulus during resting-state fMRI. Slice-timing, motion correction, and registration were performed and 72 regions-of-interest (ROIs) were extracted using Freesurfer. All calculations were done in each subject’s native space. The functional connectivity between ROIs was assessed with a Dynamic Bayesian Network (DBN) method. First, we interrogated the significant DBN connections to determine if they were influenced by either GVS stimulus compared to rest, using paired t-tests. Next, we examined the PD subjects to determine the differential effects of the different stimuli. We applied principal component analysis (PCA) to the matrix of connection strength differences, and performed multivariate linear regression analysis using UPDRS motor scores and ages as independent variables.

Results: GVS altered connectivity differently in PD and HC groups (Figure). Both stimuli affected the prefrontal cortex (PFC) connections in HC. In PD, PFC responded in a stimulus-specific manner, in contrast to ventral premotor cortex and the nucleus accumbens, which demonstrated robust effects independent of stimulus type. PCA and regression results showed that both UPDRS (p=0.02) and Age (p=0.04) were significantly correlated with the scores of the first PC, which included premotor, motor, default mode network, and insular regions.

Conclusions: Our results indicate that applying different GVS stimuli in PD can affect which functional brain connections can be modulated. We suggest that custom designing appropriate stimuli may further enhance previously-shown potential therapeutic effects of GVS by modulating disease-affected functional networks and/or potentially augmenting compensatory regions. References:

[1] Pan W, Soma R, Kwak S, Yamamoto Y. Improvement of motor functions by noisy vestibular stimulation in centralneurodegenerative disorders. J Neurol 2008;255:1657–61.

Funding: UBC/PPRI Chair in Parkinson’s Research (MJM) and a generous grant from the Mottershead Foundation

Figure: Comparison of Dynamic Bayesian Network (DBN) connections in prefrontal cortex, motor cortex and basal ganglia structures significantly modulated by different GVS stimuli (p<0.05) in PD and HC groups. (Acb, Accumbens; Cd, Caudate; DLPFC, Dorsolateral prefrontal cortex; GP, Globus Pallidum; M1, Primary motor cortex; PMd, Premotor cortex (dorsal); PMv, Premotor cortex (ventral); Pu, Putamen; SMA, Supplementary motor area; Th, Thalamus; VLPFC, Ventrolateral prefrontal cortex)

107


Investigation of an optogenetics-based multi-site motor cortical neuromodulation method for thetreatment of Parkinson’s disease

Zeyang Yu1, Janos Perge1, Wael Asaad1, 2, Arto Nurmikko1, Ilker Ozden1

1. Brown University, USA; 2. Rhode Island Hospital, USA

Background: Optogenetics, with its cellular specificity and compatibility with electrophysiology, offers unique opportunities to simultaneously monitor and modulate neural activity. While optogenetics has been utilized in studiesof Parkinson’s disease (PD), these studies did not target characteristic features of Parkinsonian pathophysiology (e.g.elevated 13-40Hz beta-band oscillations in the motor cortex). In addition to being a preferable location to probe the pathophysiology, motor cortex could also be a target for neuromodulation; as electrical deep brain stimulation(eDBS) has been suggested to exert its therapeutic effect through antidromic activation of motor cortex [1].

In our work, we address two important premises for assessment of an optogenetics-based motor cortical modulation method: (1) validation of therapeutic value of precisely targeted deep brain optogenetic modulation; (2) demonstration of potential benefits of spatiotemporally patterned optogenetic stimulation of the motor cortex bycharacterizing the spatiotemporal dynamics of pathological cortical beta-band activity.

Methods: In 6-OHDA-induced hemi-Parkinsonian (h-P) rat model, we used excitatory opsin channelrhodopsin or inhibitory opsin SwiChRCA to excite or inhibit the subthalamic nucleus (STN) while recording neural activity acrossmotor cortex with microelectrode arrays (MEAs, 5x5 or 6x6). We used behavioral assays (e.g. amphetamine-inducedrotation and mobility tests) to quantify and compare therapeutic efficacies of optogenetic stimulation and eDBS.Local field potentials (LFPs) were extracted from MEA recordings and their spatiotemporal dynamics wereexamined with spectral, correlation, and coherence analyses.

Results: Our data confirmed the presence of motor deficits such as akinesia and rotational bias in h-P rats. eDBS of STN improved these motor deficits to some extent, but not completely. In agreement with Gradinaru et al. [2],optogenetic excitation of STN did not lead to behavior improvements; by contrast we found that optogeneticinhibition of STN did alleviate akinesia and rotational bias. Further, motor cortical LFPs showed elevated betaactivity on the lesioned hemisphere. Interestingly, these oscillations were not prominent throughout all recording sites (400µm separation) but intermittently appeared only at certain locations as distinct activity patterns (Figure).

Conclusions: Single-site optogenetic modulation of STN led to behavioral improvements, but effects were limited as in eDBS. The variation of beta power across motor cortex implied inhomogeneity in the extent of Parkinsonism, andhence, potential therapeutic benefits of differential neuromodulation at different cortical sites. Therefore, our next step is to investigate the therapeutic potential of spatiotemporally-specific optogenetic modulation of motor cortex,for which we will use transparent ZnO micro-optoelectrode arrays we recently developed [3].References:[1] Li, Q., et al. (2012). Neuron 76(5): 1030-1041.

[2] Gradinaru, V., et al. (2009). Science 324(5925): 354-359.

[3] Lee, J., et al. (2015). Nature Methods 12(12): 1157-1162.

Funding: BIBS/NPNI New Frontiers Award (I.O and W.A.), NSF CBET-1402803, NSF CBET-1264816 (A.N.)

108


Title: Investigating TMS-evoked cortical responses with EEG in chronic stroke Authors: Whitney A. Gray1, Steven L. Wolf1, Michael R. Borich1

Affiliations: 1Department of Rehabilitation Medicine, Emory University School of Medicine, U.S.A

Background: Combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) to directly evoke and measure cortical activity may identify neurophysiologic biomarkers of persistent stroke-related disability1. However, TMS-evoked cortical potentials (TEPs) have not been previously characterized in chronic stroke.

Methods: Thirteen participants with chronic subcortical ischemic stroke (8 males, mean age 66±10 years, mean time post-stroke 52±29 months) and twelve healthy controls (6 males, mean age 52±15 years) completed a single TMS-EEG testing session. Real-time navigated TMS was used to identify the motor cortex hotspot and resting motor thresholds (RMT) for the abductor pollicis brevis (APB). Single suprathreshold (120% RMT) pulses were delivered while EEG signals were acquired continuously. TMS-EEG procedures were completed bilaterally. To investigate TMS-evoked local and global brain activation, amplitude and latency of known TEP components from a single channel (Cz) and global mean field power (GMFP) components across channels were extracted 30-300ms after TMS delivery. The Fugl-Meyer Upper Extremity Assessment (FM-UE) was performed in the stroke participants to measure motor impairment, where lower scores reflect greater impairment.

Multivariate (m)ANCOVAs were performed to assess differences in TEP and GMFP components between groups. RMT values were correlated with multiple TEP components and thus were included as a covariate. Bivariate relationships between EEG measures and FM-UE scores were evaluated using Pearson correlation coefficients.

Results: TEP components: A significant increase in P30, P60 and N280 component amplitudes was observed in the stroke group (all p!.001). The N45 amplitude was significantly reduced in the stroke group compared to controls (p<.001). Significantly longer latencies for P30 (p<.001) and N100 (p=.049), and a shorter P60 latency (p=.001) were detected in the stroke group (Fig.1).

GMFP: Significantly greater component amplitudes were revealed in the stroke group for P30 (p<.001), N45 (p=.017), P60 (p<.001), P180 (p<.001), and N280 (p=.011).

Behavioral: N280 amplitude was positively correlated with FM-UE score (r=0.535, p<0.001).

Conclusions: Results suggest that TEP amplitudes and latencies are different after stroke. Increased amplitudes noted for early components were not found at N100; however, the pattern of altered latencies persisted until N100. Also, greater levels of upper extremity impairment were associated with more abnormal N280 amplitudes. Early TEP components from 30-300ms are thought to be mediated by fast and slow inhibitory cortical circuits2. Future directions include investigation of the behavioral relevance of changes in activity of these circuits following stroke and the use of targeted non-invasive brain stimulation approaches to modulate cortical activity.

References: 1. Sato, S., Bergmann, T.O., Borich, M.R. Opportunities for concurrent transcranial magnetic stimulation and electroencephalography tocharacterize cortical activity in stroke. Front Hum Neurosci. 2015; 9:250. doi: 10.3389/fnhum.2015.00250.2. Ferreri, F., Rossini, P.M. TMS and TMS-EEG techniques in the study of the excitability, connectivity, and plasticity of the humanmotor cortex. Rev Neurosci. 2013; 24(4): 431-442. doi 10.1515/revneuro-2013-0019.

Funding: Dr. Gray is supported by a NIH StrokeNet research fellowship. Dr. Wolf is supported by NIH StrokeNet (5U10NS086607-03). Dr. Borich is supported by NICHD K12HD055931 and NIH grant: #5R24HD050821-11.

-10

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V)

!

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N45**

P180

N280**

P30**!!!

P60**!!

N100!!

Cz

Fig. 1: Single-channel TMS-evoked potentials (TEPs) between groups. Group-mean EEG responses recorded at the vertex (Cz) during TMS delivered over the motor cortex bilaterally in the stroke (blue) and healthy (green) groups (TMS delivery represented by red dashed line). Significant differences in TEP component amplitude and latency (i.e., time relative to TMS delivery) are depicted ["": p!0.001 for amplitude#!!: p<0.05 for latency].

109


Title: Patient-specific models of local field potentials recorded from deep brain stimulation electrodes

Authors: Nicholas Maling1, Scott Lempka2,3, Cameron McIntyre1,3

Affiliations: 1. Case Western Reserve University, Dept. of Biomedical Engineering, Cleveland, OH; 2. Cleveland Clinic Center for Neurological Restoration, Cleveland OH; 3. Cleveland VA Medical Center,

Cleveland OH

Background: Emerging innovations in deep brain stimulation (DBS) therapy increasingly utilize the recording of local field potentials (LFPs) as biomarkers of neurophysiological activity in human brains1. Nevertheless,the biophysical origin of these LFP signals remains elusive. Little is known about how the patient’s unique brain anatomy and electrode placement impact the recording of such signals. Therefore we developed a framework to theoretically analyze LFP recordings within a clinical DBS context to create an LFP model that is customized to the patient’s metrics. Methods: First, we set out to virtually recreate a patient-specific reconstruction of a subthalamic nucleus (STN) using MRI data and a-priori knowledge of STN neuronal makeup. This virtual STN was used to define the parameters of the volume conductor model, and to dictate the locations and densities of the current sources in an anatomically realistic way. We next developed models to analyze the impact of explicitly representing the DBS electrode within this LFP recording model system2. Finally we included the presence of‘subpopulations’ of highly synchronous neurons within the STN by feeding subpopulations of current sources highly correlated inputs. Results: We found that incorporating patient specific STN boundaries resulted in significant changes to LFP amplitude compared to a generic STN shape, particularly when one of the recording contacts was on or near the boundary of the STN. We also found that electrode contact size, recording configuration, and filtering effects have a substantial impact on the amplitude and frequency content of the recorded signal. Neuronal density in the area surrounding the electrode had a graded effect on LFP amplitude. A more profound effect was found by varying the synchrony of spatially discrete populations of neurons in the vicinity of the electrode. The presence and parameters of these small populations of synchronous activity had a profound effect on LFP recording characteristics when in proximity to the electrode. Conclusions: The results of our analysis are helping to identify pertinent variables that need to be considered when analyzing and interpreting LFP recordings in clinical DBS applications. Future efforts are now focused on coupling these patient-specific LFP models with chronic clinical LFP signals to further increase interpretability.

References: 1 Quinn EJ, Blumenfeld Z, Velisar A, Koop MM, Shreve LA, Trager MH, Hill BC, Kilbane C, Henderson JM, Brontë-Stewart H. Beta oscillations in freely moving Parkinson's subjects are attenuated during deep brain stimulation. Mov Disord. 2015 Nov;30(13):1750-8 2 Lempka SF, McIntyre CC. Theoretical analysis of the local field potential in deep brain stimulation applications. PLoS One. 2013;8(3):e59839Funding: NIH R01 MH10617302

110


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Rx OnlyBrief Summary: Prior to using these devices, please review the Instructions for Use for a complete listing of indications, contraindications, warnings, precautions, potential adverse events and directions for use.

SCS Indications for Use: Spinal cord stimulation as an aid in the management of chronic, intractable pain of the trunk and limbs. Contraindications: Patients who are unable to operate the system or who have failed to receive effective pain relief during trial stimulation. Warnings/Precautions: Diathermy therapy, implanted cardiac systems, magnetic resonance imaging (MRI), explosive or fl ammable gases, theft detectors and metal screening devices, lead movement, operation of machinery and equipment, postural changes, pediatric use, pregnancy, and case damage. Patients who are poor surgical risks, with multiple illnesses, or with active general infections should not be implanted. Adverse Effects: Painful stimulation, loss of pain relief, surgical risks (e.g., paralysis). The User’s Guide must be reviewed for detailed disclosure.

DRG Indications for Use: The Axium™ Neurostimulator System is indicated for spinal column stimulation via epidural and intra-spinal lead access to the dorsal root ganglion as an aid in the management of moderate to severe chronic intractable* pain of the lower limbs in adult patients with Complex Regional Pain Syndrome (CRPS) types I and II.**

*Study subjects from the ACCURATE clinical study had failed to achieve adequate pain relief from at least two prior pharmacologic treatments from at least two different drug classes and continued their pharmacologic therapy during the clinical study.

**Please note that in 1994, a consensus group of pain medicine experts gathered by the International Association for the Study of Pain (IASP) reviewed diagnostic criteria and agreed to rename refl ex sympathetic dystrophy (RSD) and causalgia, as complex regional pain syndrome (CRPS) types I and II, respectively.

Unless otherwise noted, ™ indicates that the name is a trademark of, or licensed to, St. Jude Medical or one of its subsidiaries. ST. JUDE MEDICAL and the nine-squares symbol are trademarks and service marks of St. Jude Medical, Inc. and its related companies. © 2016 St. Jude Medical, Inc. All Rights Reserved.

SJM-CPG-0316-0044 | Item approved for U.S. use only.

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NOTES

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ORGANIZING COMMITTEEBin He (Symposium Chair) University of Minnesota

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