Matthew Cook

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Cortical Computation

How does thinking work? How does the cortex compute? This is one of today's greatest mysteries in science. We do not yet know how to make machines do computations similar to the computations done with ease by animal brains. By experimenting with cortically inspired architectures, we hope to gain an understanding of how such computation can occur. One of our current directions is examining models similar to belief propagation on factor graphs, and how such models can be adapted to naturally solve learning and control problems of the sort that brains solve naturally.

Teaching

INI-434 Block: Insights Into Neuroinformatics

Publications

2014

  • Diehl, P.U. and Cook, M. Efficient Implementation of STDP Rules on SpiNNaker Neuromorphic Hardware, International Joint Conference on Neural Networks (IJCNN), 2014

2012

  • Corneil, D. and Sonnleithner, D. and Neftci, E. and Chicca, E. and Cook, M. and Indiveri, G. and Douglas, R. Real-time inference in a VLSI spiking neural network, IEEE International Symposium on Circuits and Systems (ISCAS) 2425-2428, 2012
  • Corneil, D. and Sonnleithner, D. and Neftci, E. and Chicca, E. and Cook, M. and Indiveri, G. and Douglas, R. Function approximation with uncertainty propagation in a VLSI spiking neural network, International Joint Conference on Neural Networks (IJCNN) 1-7, 2012
  • Funke, Jan and Andres, Bjoern and Hamprecht, Fred A. and Cardona, Albert and Cook, Matthew Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data , Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition 2012 1004 - 1011, 2012

2011

2010

2009

2008

2006

© 2014 Institut für Neuroinformatik