(updated on March 23th, 2017)
IEEE Brain Initiative Workshop on Advanced NeuroTechnologies for BRAIN Initiatives (ANTBI): Challenges and Opportunities
Time: 8:30 am – 17:00 pm on May 25, 2017
Workshop Chairs: Metin Akay, Paul Sajda
Workshop Program Chairs: Silvestro Micera, Jose Carmena
International Program Chairs: Nigel Lovell, Dominique Durand
The IEEE Brain Initiative Workshop on Advanced Technologies for BRAIN Initiatives, which will be held on May 25, 2017, Shanghai, China. Members of both the Neuroscience and Engineering Communities are strongly encouraged to attend this highly multidisciplinary workshop. The workshop will highlight the development of novel neuro-technologies including devices and techniques for experimental probing, neural simulation studies, and the design and development of human-machine interface systems, artificial sensors, neural implants and prosthesis have significantly restored and enhanced the impaired sensory functions and motor systems. In addition, this workshop highlights these recent technological advances by focusing on advanced technologies that monitor and control brain activities to treat neurological diseases, including Alzheimer’s, Epilepsy, Depression, etc., from the molecular to systemic levels. The workshop will also focuses on bioelectronic medicine technology which target molecular pathways and mechanism to provide better therapies for several neurological diseases as well as the global neural engineering entrepreneurship. Invited talks will be presented by internationally well respected researchers. This workshop will provide a unique interactive platform to exchange of ideas in the areas of BRAIN initiatives with leading researchers and medical and industry professionals.
Presentation title: Non-invasive human-robot interfacing for real-time interactions
Professor of Neurological Surgery and Neurology;
Director, USC Neurorestoration Center;
Surgical Director, USC Comprehensive Epilepsy Program
Dario Farina received Ph.D. degrees in automatic control and computer science and in electronics and communications engineering from the Ecole Centrale de Nantes, Nantes, France, and Politecnico di Torino, Italy, in 2001 and 2002, respectively. He is currently Full Professor and Chair in Neurorehabilitation Engineering at the Department of Bioengineering of the Imperial College London, UK. He has previously been Full Professor at Aalborg University, Aalborg, Denmark, (until 2010) and at the University Medical Center Göttingen, Georg-August University, Germany, where he founded and directed the Department of Neurorehabilitation Systems (2010-2016). Among other awards, he has been the recipient of the 2010 IEEE Engineering in Medicine and Biology Society Early Career Achievement Award, in 2012 he has been elected Fellow of the American Institute for Medical and Biological Engineering (AIMBE), and in 2014-2015 he has been Distinguished Lecturer IEEE. He has also been awarded an Advanced Grant by the European Research Council (2011-2016). His research focuses on biomedical signal processing, neurorehabilitation technology, and neural control of movement. Within these areas, he has (co)-authored approximately 400 papers in peer-reviewed Journals, which have currently received cumulatively >17,000 citations, and over 500 among conference papers/abstracts, book chapters, and encyclopedia contributions. Professor Farina has been the President of the International Society of Electrophysiology and Kinesiology (ISEK) (2012-2014) and is currently the Editor-in-Chief of the official Journal of this Society, the Journal of Electromyography and Kinesiology. He is also currently an Editor for IEEE Transactions on Biomedical Engineering and the Journal of Physiology, and previously covered editorial roles in several other Journals.
Dominique M. Durand is E.L. Linsedth Professor of Biomedical Engineering and Neurosciences and Director of the Neural Engineering Center at Case Western Reserve University in Cleveland, Ohio. He received an engineering degree from Ecole Nationale Superieure d’Electronique, Hydrolique, Informatique et Automatique de Toulouse, France in 1973. In 1974, he received a M.S. degree in Biomedical Engineering from Case Reserve University in Cleveland OH., worked several years at the Addiction Research Foundation of Toronto, Canada and in 1982 received a Ph.D. in Electrical Engineering from the University of Toronto in the Institute of Biomedical Engineering. He received an NSF Young Investigator Presidential Award as well as the Diekhoff and Wittke awards for graduate and undergraduate teaching and the Mortar board top-prof awards at Case Western Reserve University. He is a Fellow of the American Institute for Medical and Biomedical Engineering. His research interests are in neural engineering and include computational neuroscience, neurophysiology and control of epilepsy, non-linear dynamics of neural systems, neural prostheses and applied magnetic and electrical field interactions with neural tissue. He is the founder and editor-in-chief of the Journal of Neural Engineering. He has obtained funding for his research from the National Science Foundation, the National Institutes of Health and private foundations. He has published over 100 articles and he has consulted for many biotechnology companies and foundations.
Presentation title: Neural activity propagation by ephaptic coupling
Garrett B. Stanley
Garrett B. Stanley is the Flanagan Professor of Biomedical Engineering in the Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. Garrett received a bachelor’s degree in mechanical engineering with highest honors from Georgia Tech in 1992, and the M.S. and Ph.D. degrees in mechanical engineering (dynamics and controls) from the University of California at Berkeley in 1995 and 1997, respectively. From 1995 to 1997, he was an American Heart Association Predoctoral Fellow. From 1997 to 1999, he was a Postdoctoral Fellow in the Neuroscience Division of the Department of Molecular and Cell Biology at the University of California at Berkeley, and an NIH Postdoctoral Fellow. In 1999, he joined the faculty of the Division of Engineering and Applied Sciences at Harvard University, where until 2007 he was an Associate Professor of Bioengineering and an active member of the Harvard-MIT Division of Health Sciences and Technology (HST). In 2008, he joined the faculty in the Coulter Department of Biomedical Engineering at the Georgia Institute of Technology & Emory University, where he has been since. His research interests include information processing in sensory pathways, neural coding, computational neuroscience, and control theory applied to neuroscience. His research program provides a unique combination of engineering-driven research in sensory function rooted in the basic science of neural circuitry and experimental neuroscience. In 2015, he became a Fellow of the American Institute for Medical and Biological Engineering.
Presentation title: Closed-loop Optogenetic Control of the Thalamocortical Circuit
Abstract: Ca2+ signaling in astrocytes plays an important role in brain function, but these signaling events are highly variable and not well understood. To begin to fill this gap, we integrate Ca2+ imaging, quantitative data analysis, and mechanistic computational modeling to study the spatial and temporal heterogeneity of Ca2+ transients evoked by focal application of ATP. Using data and model analysis, we categorize astrocyte responses into four types. We find that responses are variable, and that the distribution of measured response types is different between somas and processes. We use the model to elucidate possible sources of Ca2+ response variability, including the temporal dynamics of IP3 and flux rates through Ca2+ channels/pumps. We also predict the effects of blocking Ca2+ channels/pumps. Finally, we propose that observed differences in response type distributions between astrocyte somas and processes can be attributed to systematic differences in the underlying biophysics.
School of Biological and Health Systems Engineering, Arizona State University, USA. http://faculty.engineering.asu.edu/santello
Marco Santello received a Bachelor in Kinesiology from the University of L’Aquila, Italy, in 1990 and a Doctoral degree in Sport and Exercise Science from the University of Birmingham (U.K.) in 1995. After a post-doctoral fellowship at the Department of Physiology (now Neuroscience) at the University of Minnesota, he joined the Department of Kinesiology at Arizona State University (ASU) (1999-2010). He is currently Professor of Biomedical Engineering, Director, and Harrington Endowed Chair at the School of Biological and Health Systems Engineering. His main research interests are motor control, learning, and biomechanics of object grasping and manipulation, neural control of hand muscles, haptics, and multisensory integration. His laboratory uses complementary research approaches, ranging from intramuscular electromyography and transcranial magnetic stimulation to motion tracking, kinetic analysis, and virtual reality environments. Dr. Santello’s research has applications to rehabilitation of sensorimotor hand function, prosthetics, and biologically-inspired robotics. Dr. Santello has published his work (100+ publications) in neuroscience and engineering journals. His research has been supported by research awards from the National Institutes of Health, the National Science Foundation, DARPA, the Whitaker Foundation, The Mayo Clinic, and Google. He has served as regular member of the Motor Function, Speech, and Rehabilitation Study Section at the National Institutes of Health, and currently serves as Associate Editor for Neuroscience and Biomedical Engineering, and member of the Editorial Board of the Journal of Assistive, Rehabilitative and Therapeutic Technologies. He is a member of the Society for Neuroscience, the Society of Neural Control of Movement, and IEEE.
Maryam M. Shanechi
Maryam Shanechi is an assistant professor and the Viterbi Early Career Chair in Electrical Engineering at the University of Southern California (USC). Prior to joining USC, she was an assistant professor at Cornell University’s School of Electrical and Computer Engineering. She received the B.A.Sc. degree in Engineering Science from the University of Toronto in 2004 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 2006 and 2011, respectively. She held postdoctoral positions at Harvard Medical School and at UC Berkeley from 2011-2013. She is the recipient of various awards including the NSF CAREER Award, the MIT Technology Review’s top 35 innovators under the age of 35 (TR35), the Popular Science Brilliant 10, and the ARO multidisciplinary university research initiative (MURI) award.
Presentation title: Multiscale Control-Theoretic Brain-Machine Interfaces
Dr. Romero is an Associate Professor of Bioengineering at the University of Texas at Dallas (UTD) and adjunct faculty in the Surgery department at the University of Texas Southwestern Medical Center (UTSW), the UTA Research Institute (UTARI) and Partner Researcher at the University of Wollongong, Australia. He received his doctorate in Neuroscience from Tulane University and postdoctoral training from UTSW as Associate Member of the Christopher Reeve Paralysis Foundation Research Consortium on Spinal Cord Injury. He has served as Director of the Regenerative Neurobiology Research Division at Texas Scottish Rite Hospital and Assistant Professor of Neurology and Plastic Surgery at UTSW. He serves as Associate Editor of Frontiers in Neuroengineering and as Founder and Chief Scientific Officer for Nerve Solutions Inc, a company that commercializes the Biosynthetic Nerve Implant and the NeuroBlock devices developed in his laboratory. He is the recipient of the 2014 UTA College of Engineering Excellence in Research Award, the 2013 TechFortWorth Impact Award and “Ten Most Promising Life Science Company Award”, and the 2013 Tech Titans Award in Technology Innovation.
Miguel A. L. Nicolelis
and Psychology and Neuroscience Co-Director, Duke Center for Neuroengineering
Presentation title: Brain-machine interfaces: from basic science to neurological rehabilitation
Abstract: In this talk, He will describe how state-of-the-art research on brain-machine interfaces makes it possible for the brains of primates to interact directly and in a bi-directional way with mechanical, computational and virtual devices without any interference of the body muscles or sensory organs. He will review a series of recent experiments using real-time computational models to investigate how ensembles of neurons encode motor information. These experiments have revealed that brain-machine interfaces can be used not only to study fundamental aspects of neural ensemble physiology, but they can also serve as an experimental paradigm aimed at testing the design of novel neuroprosthetic devices. He will also describe evidence indicating that continuous operation of a closed-loop brain machine interface, which utilizes a robotic arm as its main actuator, can induce significant changes in the physiological properties of neural circuits in multiple motor and sensory cortical areas. This research raises the hypothesis that the properties of a robot arm, or other neurally controlled tools, can be assimilated by brain representations as if they were extensions of the subject’s own body.
Paul Sajda is Professor of Biomedical Engineering, Electrical Engineering and Radiology at Columbia University. He is Director of the Laboratory for Intelligent Imaging and Neural Computing (LIINC) and Co‐Director of Columbia’s Center for Neural Engineering and Computation (CNEC). His research focuses on neural engineering, neuroimaging, computational neural modeling and machine learning applied to the study of rapid decision making in the human brain. Prior to Columbia he was Head of The Adaptive Image and Signal Processing Group at the David Sarnoff Research Center in Princeton, NJ. He received his B.S. in Electrical Engineering from MIT and his M.S. and Ph.D. in Bioengineering from the University of Pennsylvania. He is a recipient of the NSF CAREER Award, the Sarnoff Technical Achievement Award, and is a Fellow of the IEEE and the American Institute of Medical and Biological Engineering (AIMBE). He is the current the Editor‐in‐Chief for the IEEE Transactions in Neural Systems and Rehabilitation Engineering and Chair of the IEEE Brain Initiative. He is a founder/co-founder of several neurotechnology start-up companies.
Presentation title: Integrating Brain-Computer Interface Technology with Augmented and Virtual Reality
Deep Brain Stimulation: Neurodynamics, Technology and Clinical Translation
Time: 8:30 am – 11:30 am on May 25, 2017
Shouyan Wang, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China
After over 20 years clinical application of deep brain stimulation, there are still great challenges in neuroscience research in its mechanisms modulating the brain network and development of more advanced stimulation strategies. Future deep brain stimulation development needs multidisciplinary cooperation to solve for “the better treatment” and be “more beneficiary for the population”. Wearable, mobile medical technology, robotics, nano sensor technology, self-learning artificial intelligence technology, and big data analysis techniques of deep brain stimulation will promote the rapid development in the field. The clinical postoperative management moves from current hospital-oriented to family or community-based remote rehabilitation, and its clinical indications range from locomotor system diseases, degenerative neurological diseases to mental illness, as well as the autonomic nervous system diseases. Technology research and development of directional stimulation, intelligent stimulation and ultrosonic stimulation are emerging to provide more precise and specific neuromodulation. This workshop aims to promote cross-disciplinary collaboration among neuroscience, technology and clinical research in the field of modulating the human brain.
National Engineering Laboratory for Neuromodulation, Tsinghua University,
Professor Luming Li has received a B.S. degree in Mechanical Engineering (1991) and M.S. and Ph.D. degrees in Material Science and Engineering (1996) from Tsinghua University, Beijing. As a leader of a multi-disciplinary group, Professor Li has designed and created a novel deep brain stimulation device in China for patients in developing countries. To date, the Chinese DBS system, which mediates Variable Frequency Stimulation, a uniquely different function to commonly used High Frequency Stimulation, has recently been approved and certificated by the Chinese FDA (2013) following nearly ten years of R&D. Professor Li has also designed and created the first implantable, rechargeable neuromodulation device in China, which was certificated in July 2014 by CFDA and was granted with CE mark in October 2016. Recently, Professor Li also led his group in the development of the lightest Vagus Nerve Stimulator for Intractable Epilepsy treatment. This device was approved and certificated in May, 2016. These devices are now used in more than 160 clinical centers in China, with more than 3000 successful implantations in patients. Professor Li has previously been awarded with National Science Fund for Distinguished Young Scholars, 2011, “Top Ten Science & Technology Advances of Chinese College, 2012”, and the First prize of S&T, Beijing 2015. Dr. Li is currently the Director of National Engineering Laboratory for Neuromodulation and the vice chairman of Chinese Society of Neuromodulation.
Presentation title: Deep Brain stimulation and brain research
Abstract: Deep brain stimulation is the only technique that can directly modulate inside human brain using electrical stimulation. It provides great opportunities for understanding brain function in human behaviors. In the last decade, high frequency stimulation has been used for the treatment of advanced Parkinson’s disease, however, it is unable to alleviate freezing of gait and dysarthria symptoms. We have recently developed stimulation strategy of ‘Various Frequency Stimulation (VFS)’ with interleaved high and low frequency stimulation. A clinical trial results will be presented in this talk to show the significant advantages of VFS, particularly on freezing of gait. Tools and technology are essential in research of deep brain stimulation. We have established a new platform that provides both of electrical stimulation and concurrent recording of local field potentials to investigate neural circuits. This device also has great potential for providing high clinical value, such as guiding DBS parameter programming, and finally realizing the individualized therapy in closed-loop DBS. Data from ten patients will be presented in this talk to show the neural activities along sleeping stages. The findings will lead to a novel close-loop stimulation—turn off the DBS when sleeping. Another important issue in DBS therapy is MRI compatibility, which is not only essential for clinical practice but also brain research. Following numerous hardwork research in material, computation and electrical engineering, we have achieved a novel device compatible with 3T MRI, not only during off-stimulation, but also on-stimulation. This provides a significant tool to understand what happens during stimulation, essentially the mechanisms of DBS.
firstname.lastname@example.org, Medical Research Council Brain Network Dynamics Unit at the University of Oxford
Short biography: Professor Peter Brown obtained his medical degree from Cambridge University in 1984 and thereafter joined the Medical Research Council Human Movement and Balance Unit before moving to the Institute of Neurology, London. He worked as a neurologist at the affiliated National Hospital for Neurology and Neurosurgery, London, and became Head of the Sobell Department of Movement Disorders and Motor Neurophysiology at the Institute of Neurology, University College of London. He moved to the University of Oxford as Professor of Experimental Neurology in 2010, and became the director of the Medical Research Council Brain Network Dynamics Unit at the University of Oxford in 2015.
Presentation title: Novel interventional approaches to the treatment of disorders of movement in patients.
Abstract: Neurosurgeons often implant brain pacemakers to control conditions like Essential Tremor and Parkinson’s disease. The pacemakers achieve this by continuously stimulating key targets in the brain at a fixed high frequency. Such operations provide us with the opportunity to directly record from the thalamus and basal ganglia, allowing us to both infer aspects of normal functioning and to determine patterns of pathological activity. New insights may then provide the motivation for novel treatment applications or for improvements in current forms of deep brain stimulation. I will illustrate both these developments. First, I will show how primarily physiological basal ganglia signals can be decoded and potentially used to drive brain machine interfaces controlling robotic devices in paralysed patients or in amputees. Second, I will demonstrate how pathological basal ganglia signals can be used to control deep brain stimulation so that it is delivered only when necessary. Finally, I will show how pathological brain signals can sometimes be inferred from peripheral activity even when direct brain recordings are unavailable. This is the case in patients with tremor, in whom peripheral recordings of the aberrant movement can be used to control brain stimulation that specifically interacts with the underlying brain oscillations causing the problem. These new approaches to deep brain stimulation afford more efficient therapy with a wider therapeutic window.
Short biography: Prof. Shanbao Tong received the B.S. degree in radio technology from Xi’an Jiao Tong University, Xi’an, China, in 1995, the M.S. degree in turbine machine engineering, and the Ph.D. degree in biomedical engineering from Shanghai Jiao Tong University, Shanghai, China, in 1998 and 2002, respectively. From 2000 to 2001, he was a Research Trainee in the Biomedical Instrumentation Laboratory, Biomedical Engineering Department, Johns Hopkins School of Medicine, Baltimore MD, USA. He was a Postdoctoral Research Fellow in the Biomedical Engineering Department, Johns Hopkins School of Medicine from 2002 to 2005. Currently, he is a Professor in the School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China. His research interests include neural signal processing, neurophysiology of brain injury, and cortical optical imaging. Prof. Tong is the founding chairs of the IEEE EMBS Shanghai Chapter and the IEEE EMBS international summer school on neural engineering (ISSNE). Prof. Tong is also an active Associate Editor of IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Medical & Biological Engineering & Computing, Associate Editor of IEEE PULSE. He also served the Organization Committee of IEEE EMBS international neural engineering conference in San Diego (NER13) and Montpellier (NER15). Prof. Tong is the Chair of the 8th IEEE EMBS international conference of Neural Engineering (NER17) in Shanghai.
Presentation title: Transcranial Ultrasound Stimulation and its Applications
Abstract: Low intensity ultrasound is able to transmit through the skull of the head, and modulate the neuronal activities in either an inhibitory or an excitatory way, depending on the ultrasound parameters. Though the underlying mechanisms are still to be clarified, TUS has shown its advantages over the current transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) or deep brain stimulation (DBS) for its much high spatial resolution. In basic neurosciences, TUS is easier to implemented than optogenetics, with more potential for clinical translation. We are going to report how TUS can be used to modulate the neurovascular coupling to suppress or promote the hemodynamics. We applied TUS to the rodent model of ischemic brain injury, and showed that either preconditioning TUS or TUS immediately after ischemia can be neuroprotective, indicating its great potential in clinical applications.
Jianfeng.Feng@warwick.ac.uk, Department of Computer Science, Warwick University, UKInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China
Short biography: Jianfeng Feng received all his academic degrees (BSc, MSc, PhD) from Probability and Statistics Dept., Peking University, P.R, China between 1985 and 1993. Supported by the A. von Humboldt Foundation of Germany and CNR of Italy, he spent around three years in Germany and Italy between 1993 and 1996. He became a Principle Investigator at The Babraham Institute of Cambridge in 1996 and Reader in Department of Informatics of Sussex University, UK. He became a Professor of Centre for Scientific Computing and Computer Science of Warwick University in 2000. Professor Feng is the executive director of Institute of Science and Technology for Brain-Inspired Intelligence at Fudan University since 2015, which is one of the leading centres in Brain Initiative Project of Shanghai.
Presentation title: Locating the Roots in Brain Diseases
Abstract: On the therapeutic use of invasive and non-invasive brain stimulation, one of the main challenges is to locate the disease roots as precisely as possible. Using the largest datasets we have assembled in the past few years and novel statistic approaches, the roots of a few mental disorders such as schizophrenia, autism and depression are identified at the voxel level precision. In particular, in depression, we have found that the functional connectivities from medial orbital frontal cortex (OFC) which is related to pleasure are reduced, while the links from lateral OFC which is highly correlated with punishments are increased. In a follow up case study, it was confirmed that rTMS at the lateral OFC where we identified can substantially reduce the symptoms. Most interestingly, our recent results also found that drinking and smoking have the same and identical roots as depression, but alter the functional links in opposite directions. Our results could pave a new pathway for a more precise invasive and non-invasive brain stimulation in the treatments of brain diseases.
email@example.com, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Short biography: Professor Shouyan WANG received the BSc degree in Biomedical Engineering in 1994, and the MSc and PhD degree in Physiology from the Fourth Military Medical University, Xi’an, China, in 1997 and 2000, respectively. He was a Postdoctoral Research Fellow in the Neurosurgery Department of JR Hospital and Department of Physiology, Anatomy and Genetics at University of Oxford from 2002 to 2007. He worked as a Lecturer in the Institute of Sound and Vibration Research at University of Southampton from 2007 to 2012. He became a Professor of Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, and the Directors of the Biomedical Electronics Department, Key Lab of Neural Engineering and Technology at Suzhou from 2012 to 2017. Professor Shouyan Wang is currently the director of Intelligence and Neural Engineering Centre at Institute of Science and Technology for Brain Inspired Intelligence, Fudan University. His research focuses on the intelligent neuromodulation of deep brain stimulation for neurological diseases, including identification of biomarkers from human deep brain local field potentials, development of miniaturized adaptive electrical or optical stimulator, and monitoring of motor or sensory behaviors with wearables devices. Professor Shouyan Wang works toward integrating engineering, neuroscience, neurology and neurosurgery to advance the deep brain stimulation technology and clinical translation in China.
Presentation title: Function specific neuromodulation in deep brain stimulation
Abstract: Delivering stimulation related to specific functions would significantly improve the clinical outcomes of deep brain stimulation for neurological and psychiatric diseases. We conducted research toward functionally specific neuromodulation in deep brain stimulation of Parkinson’s disease through three aspects. Firstly, wearables were developed to quantify the symptoms of the patients. The wearables included five modules measuring the motion of limbs and body, and the signals were wirelessly transmitted over the distance of forty meters. The symptoms of tremor, bradykinesia and gait were quantified. Secondly, the deep brain local field potentials were characterized in three dimensions with the features of rhyming, balancing and coupling behaviors of neural oscillations. Moreover, the neural oscillations were adaptively and dynamically identified according to level of synchronization measured with patterning. The brain states were characterized with the identified multiple oscillations. Finally, a stimulation platform with recording and processing of local field potentials, EMG, EEG and motion signals was developed and it provided an interactive and integrative tool for developing intelligent neuromodulation for specific functions.
Short biography: Dr. Huiling Tan is a senior Research Scientist in Nuffield Department of Clinical Neurosciences and MRC Brain Network Dynamics Unit at the University of Oxford, UK. Dr. Tan has published highly cited papers in Brain, Journal of Neuroscience, and Experimental Neurology. Her current research interest includes: 1) the mathematical modelling of cognitive processes underlying motor behaviour; 2) the function of brain oscillations in motor control in healthy and disease; 3) neural modulation using non-invasive (tACS and TMS) and invasive stimulation techniques (DBS), as well as neurofeedback to modulate the oscillatory activities in the brain; 4) brain machine/computer interfaces (BMI/BCI) for neuroprosthetic control, rehabilitation and more advanced individualised therapy for disease.
Presentation title: Subcortical LFPs as an assistive control signal for Brain Machine Interfaces
Abstract: Brain machine interfaces (BMIs) have great potential in restoring movement/function through decoding brain signals and using the decoded information to drive external devices. However, most existing BMI systems are limited by relying on neuronal spikes and decoding is limited to kinematics only. Moreover, no human BMI user has yet achieved graded force control of a robotic hand. The basal ganglia, especially the subthalamic nucleus (STN) and globus pallidus interna (GPi), are known to be involved in the planning, execution and controlling of gripping force. Previous work from our group has shown that frequency specific activities in the local field potentials (LFPs) recorded from these structures scale with both the amplitude and speed of gripping force. In particular, we found that a first order dynamic linear model with STN LFP power changes in the gamma (55-90 Hz) and beta (13-30 Hz) bands as inputs can be used to decode the temporal profile of gripping force on individual trial basis. In a more recent study, we found that STN LFP activity was modulated by the intended force in imaginary gripping, in the absence of actual movement or proprioceptive sensory feedback. The results suggest that activities recorded from deep inside the brain may be useful for neuro-feedback or BMI control in patients who cannot move. This series of studies provides proof of concept for using deep brain local field potentials for more refined BMI control. They also lay the foundation for future studies in which we plan to use the proposed methods to decode force in real-time based on LFP signals recorded from the STN in patients. This is likely to have significant implications for developing BCI systems allowing more fine-tuning of outputs, with extra assistive information from deep brain structures.