AMARSI Adaptive Modular Architectures for Rich Motor Skills (funded by the EU for 4 years, begin in march 2010)In this new research project we will collaborate with 9 partners such as the Artificial Intellegence Lab of the University Zürich (led by Rolf Pfeifer, http://ailab.ifi.uzh.ch/pfeifer/), the Biologically Inspired Robotics Lab of the EPFL (led by Auke Ijspeert http://biorob.epfl.ch/page38158.html) on innovative learning-based solutions to difficult open research problems in robotics.If you are interested in working in this project, contact Wolfgang Maass (currently the project does not yet have a webpage, the kickoff meeting will be in mid-march). |
Brain-i-Nets Novel Brain-Inspired Learning Paradigms for Large-Scale Neuronal Networks (funded by the EU, coordinated by our Institute)Abstract: Current designs of neurally inspired computing systems rely on learning rules that appear to be insufficient to port the superior adaptive and computational capabilities of biological neural systems into large-scale recurrent neural hardware system. This is not surprising, since most of these learning rules had to be extrapolated from results of neurobiological experiments in vitro. New experimental techniques in neurobiology – such as 2-photon laser-scanning microscopy, optogenetic cell activation, and dynamic clamp techniques – make it now possible to record the changes that really take place in the intact brain during learning. First results indicate that the rules for synaptic plasticity have in fact to be rewritten. In particular, it appears that local synaptic plasticity is gated in multiple ways by global factors such as neuromodulators and network states. One primary goal of this project is to apply and extend new cutting-edge experimental techniques to produce a set of rules for synaptic plasticity and network reorganisation that describe the actual adaptive processes that take place in the living brain during learning. |
ORGANIC Self-organized
recurrent neural learning for language processing (funded by the EU)
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SECO Self-Constructing Computing Systems (funded by the EU)Abstract of the research project: SECO is a four-year project funded by the Seventh Research Program (FP7) of the European Union. It involves 7 research groups in 5 countries. SECO is one of several projects funded under the FP7 initiative on BIO-ICT Convergence. SECO (short for Self Construction) will propose methods for designing and implementing self-constructing systems. It will begin by examining existing self-constructing systems such as the mammalian neocortex, and move towards a theoretical framework for abstract specification of arbitrary self-constructing systems.As circuits get exponentially smaller and faster, we face exponential increases in their production cost. Current hardware methodologies demand extremely low failure rates for individual components, yet when fabricating huge circuits, yields are still low. Nature has solved these problems. Our neocortex, a cellular computer that generates intelligent behavior, constructs and configures itself starting from a single precursor cell, based on genetic information and interactions with its environment. Understanding this process would revolutionize computer technology. Progress in developmental neuroscience now permits a reverse-engineering approach, abstracting nature's principles into systems of our own design. Here we propose some first steps towards understanding these developmental construction mechanisms so that we can transpose them into novel software design technologies. We will demonstrate, by a fusion of experimental neuroscience, detailed physical simulation, and theoretical analysis, the principles by which a population of real or artificial neurons can grow and assemble themselves into functioning circuits. |
FACETS Fast Analog Computing with Emergent Transient States (funded by the EU)Abstract of the research project: Information science has been a major driving force of the economical and social development in the 20th century. Based on the ingenious concept of Alain Turings universal computing machine and the availability of semiconductor based transistors, the IT industry has been able to follow an aggressive roadmap of ever increasing performance according to power laws like the well known Moore's Law. It appears to be a matter of time only until computers will eventually reach the capabilities of the human brain.Upon closer inspection, however, the brain is dramatically different from conventional computers. The differences are not only due to the use of biological tissue rather than silicon but also in terms of the computing architecture. The brain is not composed out of highly specialized and separated building blocks like a microprocessor but exhibits a rather uniform structure. It does not use Boolean operations like ANDs and ORs to perform logical operations on well defined stable states but involves the dynamics of transient states to code and to process information. Maybe most importantly, there is no engineered software to deal with pre-defined situations. Instead, the brain is based on a huge number of truly massively parallel non-linear processing elements (neurons), a very high connectivity (synapses) and self-organisation (learning, plasticity). The FACETS project aims to address the unsolved question of how the brain computes with a concerted action of neuroscientists, computer scientists, engineers and physicists. It combines a substantial fraction of the European groups working in the field into a consortium of 13 groups from Austria, France, Germany, Hungary, Sweden, Switzerland and the UK. About 80 scientists will join their efforts over a period of 4 years, starting in September 2005. A project of this dimension has rarely been carried out in the context of brain-science related work in Europe, in particular with such a strong interdisciplinary component. |
FACETS-ITN: Phd-Program: From Neuroscience to Neuro-Inspired Computing
Two Phd-positions are available at our Institute within this
interdisciplinary training project for research on Neuro-inspired
computing and learning. If you are interested in these positions, send
email with vita etc to Wolfgang Maass maass@igi.tugraz.at |
| In addition our institute is
member of the EU-network of
excellence PASCAL -
Pattern
Analysis, Statistical Modelling and Computational Learning. |