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. |
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. |
BrainScaleS - Brain inspired multiscale computation in neuromorphic hybrid systems (funded by the EU)Abstract:The BrainScaleS project aims at understanding function and interaction of multiple spatial and temporal scales in brain information processing. The fundamentally new approach of BrainScaleS lies in the in-vivo biological experimentation and computational analysis. Spatial scales range from individual neurons over larger neuron populations to entire functional brain areas. Temporal scales range from milliseconds relevant for event based plasticity mechanisms to hours or days relevant for learning and development. In the project generic theoretical principles will be extracted to enable an artificial synthesis of cortical-like cognitive skills. Both, numerical simulations on petaflop supercomputers and a fundamentally different non-von Neumann hardware architecture will be employed for this purpose. Neurobiological data from the early perceptual visual and somatosensory systems will be combined with data from specifically targeted higher cortical areas. Functional databases as well as novel project-specific experimental tools and protocols will be developed and used. New theoretical concepts and methods will be developed for understanding the computational role of the complex multi-scale dynamics of neural systems in-vivo. Innovative in-vivo experiments will be carried out to guide this analytical understanding. Multiscale architectures will be synthesized into a non-von Neumann computing device realised in custom designed electronic hardware. The proposed Hybrid Multiscale Computing Facility (HMF) combines microscopic neuromorphic physical model circuits with numerically calculated mesoscopic and macroscopic functional units and a virtual environment providing sensory, decision-making and motor interfaces. The project also plans to employ petaflop supercomputing to obtain new insights into the specific properties of the different hardware architectures. A set of demonstration experiments will link multiscale analysis of biological systems with functionally and architecturally equivalent synthetic systems and offer the possibility for quantitative statements on the validity of theories bridging multiple scales. The demonstration experiments will also explore non-von Neumann computing outside the realm of brain-science. BrainScaleS will establish close links with the EU Brain-i-Nets and the Blue Brain project at the EPFL Lausanne. The consortium consists of a core group of 10 partners with 13 individual groups. Together with other projects and groups the BrainScaleS consortium plans to make important contributions to the preparation of a future FET flagship project. This project will address the understanding and exploitation of information processing in the human brain as one of the major intellectual challenges of humanity with vast potential applications. The BrainScaleS project builds on the research carried out in the FACETS project (2005-2010) and will for the planned student education work together with the Marie-Curie initial training network FACETS-ITN. |
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. |
FWF |