Aimed at early postgraduates in the field of Biomedical Engineering – specifically in Neural Engineering
The event will take place from 19th-21st September at the Institute of Digital Healthcare, University of Warwick, and will bring together early postgraduates and respected mentors in various areas and disciplines underpinning neural engineering – from neural interfacing, modelling, computational intelligence, neuro-rehabilitation and neural-networks/cybernetics. The purpose of this event is to help in the development of careers of postgraduates by leading them into the best ways of using discussion of papers in a conference and so to improve networking, it also gives young researchers an opportunity to showcase their work and widen their network within the community. An outcome of the meeting will be the production of a UK position report on Neural Engineering.
Interested postgraduates are invited to submit a brief abstract (250 words), before 4th June 2012, in one of the following areas covered by the programme:
- Biological/technology interfaces (implantable cortical interfaces and scalp electrodes), including biomaterials; neural signalling; electrode design, etc.
- Neural prosthesis
- Functional neuroimaging: electrophysiological (EEG, SEEG, MEG), (f)MRI, PET etc.
- Neural communication (brain-computer interfacing)
- Neural signal processing and modelling
- Cognitive engineeringNeural informatics
The programme for the event will consist of a mix of invited talks by a small number of experts in various fields within Neural Engineering, and early postgraduates in the field.
If you are interested in attending, please register interest at c dot m dot shepherd at warwick dot ac dot uk and submit your 250 word abstract to the same email address before 4th June 2012.
The event itself is sponsored by the Royal Academy of Engineering, and is therefore free – interest is expected to be high and places will be limited so please act now.
|Prof Paulo Lisboa, Professor of Industrial Mathematics at Liverpool John Moores University||
Neural Signal Processing and Modelling
Professor of Healthcare Technology and Director of the Institute of Digital Healthcare at the University of Warwick.
He is a Senior Member of the Institute of Electrical and Electronic Engineering (IEEE), Fellow of the Institution of Engineering Technology (IET) and Fellow of the Royal Society of Medicine (RSM). He is Chair of the IEEE Engineering in Medicine and Biology Society UKRI Chapter and is European rep. on IEEE EMBS ADCOM. He is Chair of the IEEE UKRI Section Executive committee and is immediate past chair of the IET Healthcare Technology Professional Network Executive committee.
He obtained his PhD in Biomedical Engineering from the University of Canterbury, New Zealand in 1997 following the prestigious award of a Commonwealth Scholarship. Prof James’ research concerned advances in neural computing techniques for the analysis of epileptiform discharges in the EEG. Between 1997 and 1999 he was awarded a post-doctoral research fellowship at the Montreal Neurological Institute and Hospital, McGill University, Canada where he furthered his research into seizure analysis and the understanding of neurophysiological processes. This was then followed by the award of a post-doctoral research fellowship at Aston University between 1999 and 2001. During this time, he extended his novel analysis techniques to magnetoencephalographic (MEG) studies as well as epileptiform EEG. From March 2001 until December 2003 he was appointed a Lecturer within the Neural Computing Research Group at Aston University. He was then appointed as Lecturer in Biomedical Signal Processing at the University of Southampton in January 2004 and then a Reader in Biomedical Signal Processing in 2006. In 2010 he joined the University of Warwick at his current post.
Prof James’ current research activity centres on the development of biomedical signal and pattern processing techniques for use as diagnostic or prognostic tools in the treatment of disorders of the human body. Primarily his work has concentrated on the development of processing techniques applied to the analysis of the electromagnetic (EM) activity of the human brain, particularly in a functional neuroimaging context. Much of his research has been devoted to creating automated analysis techniques for the analysis of EEG data in epilepsy – these include automated spike and seizure detection algorithms, EEG (and MEG) de-noising algorithms and seizure onset prediction algorithms. He is particularly interested in the development of techniques of Blind Source Separation (BSS) and Independent Component Analysis (ICA) for EM brain signal analysis such as denoising, source identification and extraction, and for the automation of such algorithms for clinical use. He also has a particular interest in the ongoing development of these inherently multi-channel techniques and how then can be used in a single-channel environment, this is a very practical issue with devices that are to be worn in an ambulatory setting. Significant advances have been made in this area allowing these very powerful BSS techniques to be used to extract multiple underlying sources from just single (or very few) recording channels.
He was co-founder of the Southampton Brain-computer Interfacing (BCI) Research Programme and now leads the BCI Lab at the IDH, University of Warwick. Through this interaction at the LSI Dr James’ research is being applied in the biomedical fields of epilepsy research; Brain-Computer Interfacing; EEG denoising for evoked potentials analysis (BCI and use with Cochlear Implants); EEG/MEG slow-wave analysis for ADHD diagnosis and understand; heart and lung sound detection and identification; pattern processing of electrophysiological signals from C.elegans as well as their behavioural monitoring through image processing; as well as Monitoring the well-being of psychiatric patients in their home environment using Pervasive Ambient Monitoring (PAM).
Prof James is Primary Investigator (PI) leading on EPSRC Grant EP/F005091/1 (a multi-partner grant involving the Universities of Southampton, Nottingham and Stirling) on monitoring psychiatric patients at home through Pervasive Ambient Monitoring (Enabling health, independence and wellbeing for psychiatric patients through PAM); he is CI on BBSRC/MRC Grant BB/E022251/1 (in collaboration with the Schools of Biological Sciences and Psychology at Southampton) on Exploiting C. elegans to provide insight into the neural substrates of human alcohol dependence. Prof James was on the steering committee of the EPSRC Independent Component Analysis Research Network (EPSRC Grant EP/C005554/1). He was PI of EPSRC Grant GR/13132 on seizure onset prediction in EEG, and a part of EPSRC Grant GR/L94673 (Signal processing for MEG). He was PI on Royal Society funded International Incoming and Outgoing Short Visits between himself and collaborators in the University of Valladolid, Spain researching non-linear analysis techniques for seizure onset prediction in epilepsy from brain signal recrodings. He has also been awarded an ICUK Partnership Grant to investigate collaborative efforts on brain-computer interfacing with researchers at Tsinghua University, Beijing, China.
David Willshaw is Professor of Computational Neurobiology at the University of Edinburgh, UK. Since 2001, he has co-ordinated neuroinformatics research in the UK. Currently, he is the UK Scientific Representative of the International Neuroinformatics Co-ordinating Facility (INCF), which is a professional organisation devoted to advancing the field of neuroinformatics, as well as being Co-ordinator of the UK INCF Node.
He is the grant holder of the Edinburgh Doctoral Training Centre in Neuroinformatics and Computational Neuroscience funded by EPSRC in association with MRC and BBSRC.
Since 2002, this Centre has trained over 80 PhD students from the physical and informational sciences who are applying quantitative approaches to neuroscience and to neurally-inspired computing.
His research has focussed on neural networks and computational neuroscience, stretching back over 35 years with over 100 scientific papers. This has included a spell of combining experimental work with modelling approaches. He has worked in a variety of research areas including modelling of (i) associative memory storage in the hippocampus, (ii) of the functioning of basal ganglia, particularly the subthalamic nucleus, and (iii) the development of patterned nerve connections in the visual and neuromuscular systems.
He has also developed algorithms for combinatorial optimisation (with Richard Durbin he developed the Elastic Net algorithm for the Travelling Salesman Problem). In his current research, he leads a multi-centre Wellcome Trust funded project combining modelling approaches to investigate the roles of neural activity and molecular signalling in the formation of ordered nerve connections in the mouse retinocollicular system.
Since 1984, he has held long term research support from the UK Medical Research Council and the Wellcome Trust.
He was the recipient of the IEEE Neural Networks Council Pioneer Award in 1992.
From 1999-2005, he was Editor-in-Chief of the computational neuroscience journal Network: Computation in Neural Systems.
With colleagues, he has just published a Cambridge University Press text book Principles of Computational Modelling in Neuroscience.
Edward Tarte graduated in 1988 with a BSc (Hons) in Physics from the University of Bristol. He went on to study for a PhD in the physics of superconducting devices at the University of Cambridge. He continued this research between 1992 and 1995 as a Post-Doc in the Cambridge Materials Science and Metallurgy department. In 1995 he was appointed as a Senior Assistant in Research in the Cambridge Physics department, where he began working on Superconducting Quantum Interference Devices (SQUIDs). In 2000 he was awarded an EPSRC Advanced Fellowship in the Materials Department in Cambridge. During this period, he investigated the use of SQUID sensors to detect neuronal activity in-vitro. Edward moved to Birmingham in 2005 as a University Research Fellow, where his interest in the detection of bioelectric phenomena developed into a major part of his research program. His team developed an electrical interface for the peripheral nervous system, in collaboration with colleagues in Cambridge and King’s College in London, which has been patented. Other ways of applying the same technology to bioelectric phenomena are being developed as well as the use of nanofabrication techniques to improve the performance of such devices. He was elected a Fellow of the Institute of Physics in 2008.
Dr Tarte is interested in the application of the ideas and techniques of electrical engineering to biomedical science. In particular, he has used microfabrication and nanofabrication techniques to construct a number of devices designed to detect bioelectric signals. These have included devices designed to detect both biomagnetic fields and biopotentials associated with neural currents in brain tissue slices and electrode arrays for interfacing to peripheral nerves for use in prosthetic applications. The development of these devices has required him to consider issues such as the mechanisms governing the generation of bioelectric signals by excitable tissues and the electrical properties of those tissues at the cellular and continuum level. In addition the nanostructure of the interface between a measurement electrode and extracellular fluid determine its electrode performance and the immune response of tissue to the presence of an implant. This has led to the development of techniques for nanostructuring the surface of implant materials.
In order to conduct research in this area of biomedical electrical engineering, Dr Tarte has built up facilities which allow him to fabricate, package and electrically characterise electrode arrays based on biocompatible polymers such as polyimide. These facilities were developed for the fabrication of the Spiral Peripheral Nerve Interface (SPNI), but Dr Tarte has also worked on arrays of penetrating electrodes for cortical applications. Polymers have the advantage over materials such as silicon of a lower Young’s modulus, which results in more flexible and softer devices, better matched to the mechanical properties of nervous tissue. The flexibility makes it possible to construct devices such as the SPNI which is fabricated using photolithography as a flat structure on a silicon handle wafer and then rolled to fit the three dimensional structure of a nerve. This device contains channels, into which regenerating nerve fibres grow, with electrodes in the base. These channels not only guide the fibres past the electrodes, the confinement of the extracellular fluid causes the voltage detected by the electrodes to be enhanced. Dr Tarte is interested in investigating other applications of polymer based electrode arrays such as surface electrodes for electrocorticography or penetrating electrodes containing microfluidic channels for drug delivery.
Professor Richard Bayford MSc, PhD (MIEEE, FInstP, FInstIPEM) is the Head of Biophysics at the Middlesex University Centre for Investigative Oncology, Professor of Bio-modeling and Informatics and Head of Departmental Research, Middlesex University and Honorary Senior Lecturer, Department of Electrical and Electronic Engineering, University College London.
Bayford’s expertise is in biomedical imaging, bio-modelling, electrical impedance tomography (EIT), nanotechnology, deep brain stimulation, tele-medical systems, instrumentation and biosensors. He pioneered the first reconstruction algorithm to image impedance changes inside the human head. He has worked as PI on many EPSRC, EU and industrial sponsored research projects. He has been the director of a major EPSRC Nanotechnology Grand Challenges Healthcare project (EP/G061572; “New imaging methods for the detection of cancer biomarkers” £1.7M). This project involved collaboration with Midatech Ltd. (a leading nanotechnology company headed by Professor Tom Rademacher) and Zilico Ltd.; Midatech are now funding one of our research projects and Zilico are providing equipment. He co-ordinated a major ten-tel EU project, Medical Diagnosis, Communication and Analysis Throughout Europe (MEDICATE) to develop a system to identify links between Asthma and air quality. This project included the two companies, Jarger (now known as Carefusion) and Cable and Wireless. He has also had past collaborations with Medtronic who have provided DBS electrodes for research projects. His principle area of research focuses on the development of image reconstruction algorithms and hardware development for imaging brain function.
He has had long collaborations with multidisciplinary research groups both in the UK and overseas on biomedical applications of EIT and bio-impedance. He has published over 200 scientific papers. He has been guest editor on three special issues and co-organizer of three conferences on biomedical applications of EIT. He is the Editor-in-Chief of the IoP Physiological Measurements journal, a member of the editorial board of the International Journal of Biomedical Imaging and Chairs the Publication committee for IPEM. Invited Keynote lectures include: BIOSTEC 5th international joint conference on Biomedical Engineering System and Technologies, Vilamoura, Portugal; 1st Symposium on Systems Approaches to Parkinson's Disease (SAPD) hosted by the Hamilton Institute, Maynooth National University of Ireland; Basic Electrical Impedance Tomography for the XIVth International Conference on Electrical Bioimpedance and the 11th Conference on Biomedical Applications of EIT, Florida University USA. Invited lectures at the Universities in Tianjing China on EIT and DBS, and the Philosophy of Brainy EIT Algorithms, ICEBI XII-EITV Gdansk, Poland.
Paulo Lisboa studied Mathematical Physics at Liverpool University, taking a PhD in theoretical particle physics in 1983. He is Professor in Industrial Mathematics and heads the Department of Mathematics and Statistics in the School of Computing and Mathematical Sciences at Liverpool John Moores University.
He holds cross-Faculty positions as chair of the executive committee of the Centre for Health and Social Care Informatics and co-lead of the Medicine and Therapeutics Network in the Institute for Health Research.
His research is focused on computer-based decision support in healthcare, the analysis of public health data for policy reporting and commissioning purposes, and computational data analysis in a range of applications including sports medicine and computational marketing. Particular aspects include principled approaches to case-based retrieval of reference cases, source identification in Magnetic Resonance Spectroscopy, flexible models for hazard estimation following surgery for breast cancer and scalable conditional independence maps for multimodal data fusion.
He has over 200 refereed publications with awards from the journal Neural Networks for most cited article 2006-10 and most downloaded article in 2003.
He chairs the Medical Data Analysis Task Force in the Data Mining Technical Committee of the IEEE-CIS and is Associate Editor for Neural Networks, IET Science Measurement and Technology, Neural Computing Applications, Applied Soft Computing and Source Code for Biology and Medicine. He is also a member of the EPSRC Peer Review College and an expert evaluator for the European Community DG-INFSO.
Simon Schultz is Senior Lecturer, and Royal Society Industry Research Fellow, in the Department of Bioengineering at Imperial College London. He trained in physics and electrical engineering, before completing a DPhil in computational neuroscience at Oxford University in 1998. This was followed by postdoctoral stints in experimental neuroscience with Tony Movshon at New York University, and Michael Häusser at UCL. He joined Imperial College in 2004, and has led the development of Imperial’s critical mass in the area of Neurotechnology. He is widely known for work on neural coding. He has been amongst the pioneers in the use of two-photon imaging to study neural coding and has also worked on large-scale computational models of cortical circuits. He is the Chair of Imperial’s Neuroscience Technology Network, and PI of the Imperial College node of the new EU Marie-Curie Training Network “Neural Engineering Transformative Technologies”. He is Associate Editor for the Journal of Computational Neuroscience, and serves on the National Committee of the British Neuroscience Association as Membership Secretary.
His research group aim to understand how sensory information is processed by neural circuits in the mammalian cerebral and cerebellar cortices, including how it is used in elementary cognitive operations. Understanding how the “cortical circuit” processes information will help us to understand how it dysfunctions in brain disorders, and will also aid in the design of novel computational devices and brain-machine interface technologies. The Schultz research group do both neuroscience experiments, primarily in mouse models, and theoretical/computational work. They use a number of technologies to probe cortical circuit function – two photon calcium imaging, optogenetic disruption of genetically targeted cells, and electrophysiology. They also develop novel algorithms, particularly based on information theory, for analysing the resulting high-dimensional datasets. More information can be found at http://www.schultzlab.org
Timothy Griffiths is Wellcome Senior Clinical Fellow and Professor of Cognitive Neurology at Newcastle University. His research concerns human complex sound processing; the analysis of auditory patterns relevant to speech, music and environmental-sound analysis. He studies deficits in complex sound processing in patients with brain lesions, functional imaging data (fMRI and MEG) from normal subjects, and depth electrode data from the auditory cortex of neurosurgical patients. The functional imaging is carried out at the Wellcome Trust Centre for NeuroImaging in London, where he is a Principal, and the depth electrode data is acquired at Iowa where he is adjunct Professor. These studies allow inference about normal complex-sound processing mechanisms. Other work explores abnormal complex-sound analysis in developmental and degenerative disorders, and brain mechanisms for tinnitus and auditory hallucinations.