IEEE Life Sciences Newsletter
This issue of the IEEE Life Sciences Newsletter brings you some very interesting and leading-edge information on the intersection between fundamental neuroscience research and electronic engineering. The May issue of the Proceedings of the IEEE was a special issue entitled "Engineering Intelligence Electronic Systems Based on Computational Neuroscience". In an overview article, Dr. Mark McDonnell, who co-edited that issue, summarizes the context and contributions of the Special Issue. We also present three papers that summarize contributions to the Special Issue with particular relevance to life sciences in respect of neuroscience. We especially wish to thank Dr. McDonnell, a Senior Member of IEEE, for arranging for these articles.
Special Issue of Proceedings of the IEEE highlights the contributions of Electronic Engineering to Computational Neuroscience
By Mark D McDonnell
In May 2014, Proceedings of the IEEE published a Special Issue focused on elucidating the rapidly growing intersection between electronic engineering and the scientific field of computational neuroscience . This field is an interdisciplinary area of scientific research in which one of the primary goals is to understand how electronic activity in brain cells and networks enables biological intelligence.
By Nicolas Franceschini
For several decades, engineers and biologists have attempted to harness animals' sensory-motor intelligence to build autonomous machines. In the May 2014 issue of Proceeding of the IEEE, devoted to Engineering Intelligent Electronic Systems Based on Computational Neuroscience, the author describes how microoptical, behavioral and electrophysiological experiments carried out on insects have led to building seven proof-of-concept robots equipped with insect-derived neuromorphic sensors and autopilots. These constructions in turn are used to better apprehend the clever tricks used by insects, which negotiate their complex environments with a level of agility that greatly outpasses that of both vertebrate animals and present-day aerospace robots.
By Mostafa Rahimi Azghadi, Giacomo Indiveri, and Derek Abbott
Neuromorphic engineering attempts to understand the computational properties of neural processing systems by building electronic circuits and systems that emulate the principles of computation in the neural systems. The electronic systems that are developed in this process can serve both engineering and life sciences in various ways ranging from low-power brain-like computing embedded systems to neural-based control, brain machine interfaces, and neuroprosthesis. To realize such systems, various approaches and strategies with their own advantages and limitations, may be adopted. Here, we provide a summary of our recent article published in the proceedings of the IEEE , where we have discussed and reviewed the various approaches to the design and implementation of neuromorphic learning systems, and pointed out challenges and opportunities in these systems.
By Terrence C. Stewart and Chris Eliasmith
We review the methods used to construct Spaun, the first biologically detailed brain model capable of performing cognitive tasks. Spaun has 2.5 million simple, spiking neurons with 60 billion connections between them. These neurons are arranged to respect known anatomical and physiological constraints of the mammalian brain. The resulting model can perform eight different perceptual, motor, and cognitive tasks (see http://nengo.ca/build-a-brain/spaunvideos for video demonstrations). We built Spaun using Nengo, our general-purpose tool set for building systems that compute using neuron-like components in a biologically constrained manner. Building such systems is critical for improving our understanding of how the brain works, and to make use of recent advances in neuromorphic hardware.
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The IEEE Life Sciences Newsletter is a new initiative to bring forth interesting articles and informative interviews within the exciting field of life sciences every month. Please subscribe to the newsletter to receive notification each month when new articles are published.
June 2014 Contributors
Mark D. McDonnell is a Senior Research Fellow at the Institute for Telecommunications Research, University of South Australia, where he is Principle Investigator of the Computational and Theoretical Neuroscience. He received a PhD in Electronic Engineering from The University of Adelaide, Australia His interdisciplinary research focuses on the application of computational and engineering methods to advance scientific knowledge about the influence of noise and random variability in brain signals and structures during neurobiological computation. Read more
Nicolas Franceschini received the Doctorat d'Etat degree in physics from the University of Grenoble and National Polytechnic Institute, Grenoble, France. He was appointed as a Research Director at the C.N.R.S. and set up the Neurocybernetics Lab, and later the Biorobotics Lab in Marseille, France. His research interests include neural information processing, vision, eye movements, microoptics, neuromorphic circuits, sensory-motor control systems, biologically-inspired robots and autopilots. Read more
Mostafa Rahimi Azghadi is a PhD candidate in the University of Adelaide, Australia. His current research interests include neuromorphic learning systems, spiking neural networks and nanoelectronic. Read more
Giacomo Indiveri is an Associate Professor at the Faculty of Science, University of Zurich, Switzerland. His current research interests lie in the study of real and artificial neural processing systems and in the hardware implementation of neuromorphic cognitive systems, using full custom analog and digital VLSI technology. Read more
Derek Abbott is a full Professor within the School of Electrical and Electronic Engineering at the University of Adelaide, Australia. His interests are in the area of multidisciplinary physics and electronic engineering applied to complex systems. Read more
Terrence C. Stewart received a Ph.D. degree in cognitive science from Carleton University in 2007. He is a post-doctoral research associate in the Department of Systems Design Engineering with the Centre for Theoretical Neuroscience at the University of Waterloo, in Waterloo, Canada. His core interests are in understanding human cognition by building biologically realistic neural simulations, and he is currently focusing on language processing and motor control. Read more
Chris Eliasmith received a Ph.D. degree in philosophy from Washington University in St. Louis in 2000. He is a full professor at the University of Waterloo. He is currently Director of the Centre for Theoretical Neuroscience at the University of Waterloo and holds a Canada Research Chair in Theoretical Neuroscience. He has authored or coauthored two books and over 100 publications in philosophy, psychology, neuroscience, computer science, and engineering venues. Read more