Björn Kindler

Daniel Brüderle, Dr. rer. nat. 2009

Status: Alumnus

Contact

mail(at)danielbruederle.de

Collaborative Tasks

  • Coordination of software development in the Electronic Vision(s) group and of software collaborations with partners
  • Integration of FACETS project results into a novel neuroscientific modeling work flow for the FACETS hardware devices

Research

  • Development of an experimental interface for a neuromorphic hardware system
  • Emulation of cortical network models with a wafer-scale neuromorphic hardware system (description, network topology and parameter mapping, stimulation, recording, analysis)
  • Neural network modeling: hardware - software comparison studies
  • Statistical analysis of neural network dynamics

Further Interests

  • Self-organization and synaptic plasticity
  • Liquid computing
  • Pattern recognition with neural networks

Theses

Articles and Peer-reviewed Conference Papers

2011

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

Biological Cybernetics, Volume 104, Issue 4 (2011), pp. 263-296 doi: 10.1007/s00422-011-0435-9 Preprint available from arXiv:1011.2861v2 [q-bio.NC]

2010

Compensating Inhomogeneities of Neuromorphic VLSI Devices via Short-Term Synaptic Plasticity

Frontiers in Computational Neuroscience 4:129 (2010) doi:10.3389/fncom.2010.00129

Simulator-Like Exploration of Cortical Network Architectures with a Mixed-Signal VLSI System

Proceedings of the 2010 IEEE International Symposium on Circuits and Systems, Paris, France, pp. 2784-2787

A Wafer-Scale Neuromorphic Hardware System for Large-Scale Neural Modeling

Proceedings of the 2010 IEEE International Symposium on Circuits and Systems, Paris, France, pp. 1947-1950

A software framework for mapping neural networks to a wafer-scale neuromorphic hardware system

Proceedings of the 2010 Artificial Neural Networks and Intelligent Information Processing, Madeira, Portugal, pp. 43-52

A common language for neuronal networks in software and hardware

The Neuromorphic Engineer (online article 2010) doi: 10.2417/1201001.1712

2009

Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System

Frontiers in Neuroinformatics 3:17 (2009) doi:10.3389/neuro.11.017.2009

High-Conductance States on a Neuromorphic Hardware System Bernhard Kaplan, Daniel Bruederle, Johannes Schemmel and Karlheinz Meier Proceedings of the 2009 International Joint Conference on Neural Networks, Atlanta, USA

2008

PyNN: a common interface for neuronal network simulators

Frontiers in Neuroinformatics 2:11 (2008) doi:10.3389/neuro.11.011.2008

2007

A Software Framework for Tuning the Dynamics of Neuromorphic Silicon Towards Biology Daniel Bruederle, Andreas Gruebl, Karlheinz Meier, Eilif Mueller, and Johannes Schemmel Modeling Synaptic Plasticity within Networks of Highly Accelerated I&F Neurons Johannes Schemmel, Daniel Bruederle, Karlheinz Meier, Boris Ostendorf Proceedings of the 2007 IEEE International Symposium on Circuits and Systems, New Orleans, USA

2006

Achieving Compatible Numeral Handwriting Recognition Rate by a Simple Activation Function Daniel Bruederle, Khamron Sunat, Sirapat Chiewchanwattana, Chidchanok Lursinsap, Suchada Siripant International Journal of Computational Intelligence Research (IJCIR) Special Issue: Neurocomputing and Applications, Volume 2, Issue 1, pp. 1-9, ISSN 0973-1873

2004

On the Evolution of Analog Electronic Circuits Using Building Blocks on a CMOS FPTA

Springer LNCS 3102 Proceedings of the 2004 Genetic and Evolutionary Computation Conferene, Seattle, USA, ISBN: 3-540-22344-4, pp. 1316-1327

Further Abstracts and Presentations

2011

Ten thousand times faster: Classifying multidimensional data on a spiking neuromorphic hardware system (Bernstein Center Poster Award)

BC11: Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting, Freiburg, Germany, October 4 - 6, 2011 (Available from Nature Precedings)

Sparse approximation on a network of locally competitive integrate and fire neurons

COSYNE 2011, Salt Lake City, Utah, USA, February 28 - March 1, 2011

2010

FACETS: From Neurobiology to Neuromorphic computing - Cutting Edge Research and Interdisciplinary Graduate Training Daniel Bruederle, Andread Gruebl, Bjoern Kindler, Karlheinz Meier ICT Event 2010, Brussels, Belgium, September 27 - 29, 2010

Simulator-Like Exploration of Cortical Network Architectures with a Mixed-Signal VLSI System

2009

Matching Network Dynamics Generated by a Neuromorphic Hardware System and by a Software Simulator

Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, September 30 - October 02, 2009

NeuralEnsembleOrg: Unifying neural simulators in Python to ease the model complexity bottleneck

2nd INCF Congress of Neuroinformatics, Pilsen, Czech Republic, September 06 - 08, 2009

Towards a New Computational Paradigm: Mapping Biological Neural Networks onto Neuromorphic Hardware

European Future Technologies Conference, Prague, Czech Republic, April 21-23, 2009

2008

Fast Analog Computing with Emergent Transient States Daniel Bruederle, Bjoern Kindler, Jens Kremkow, Noelle Lewis, Richard Naud ICT Event 2008, Lyon, France, November 25 - 27, 2008

NeuroTools: analysis, visualization and management of real and simulated neuroscience data Jens Kremkow, Thierry Brizzi, Daniel Bruederle, Andrew Davison, Eilif Muller, Laurent Perrinet, Michael Schmuker, Pierre Yger Neuroscience 2008, Washington DC, November 16 - 19, 2008

PyNN: a common interface for neuronal network simulators

Neuroinformatics 2008, Stockholm, Sweden, September 07 - 09, 2008

Accelerated Neuromorphic Hardware in the FACETS Research Project Daniel Bruederle, Bjoern Kindler, Johannes Schemmel, Karlheinz Meier 4th International Nanotechnology Conference on Communication and Cooperation (INC4), Tokyo, Japan, April 14-17, 2008

2007

Verifying the biological relevance of a neuromorphic hardware device

16th Annual Computational Neuroscience Meeting (CNS 2007), Toronto, Canada. 7-12 July 2007

EU-Forschungsprojekt FACETS: Massiv parallele neuronale Netze in Hardware Daniel Bruederle, Bjoern Kindler, Johannes Schemmel, Karlheinz Meier

Supervised Student Work

Last update of this page: 2011-01-01