Publications

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Buesing, L., and W. Maass, "Simplified rules and theoretical analysis for information bottleneck optimization and PCA with spiking neurons", NIPS 2007: Advances in Neural Information Processing Systems, vol. 20: MIT Press, 2008, 2007. Abstract
Buonomano, D., and W. Maass, "State-dependent computations: Spatiotemporal processing in cortical networks", Nature Reviews Neuroscience, vol. 10, no. 2, pp. 113-125, 2009. Abstract
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Haeusler, S., K. Schuch, and W. Maass, "Motif distribution and computational performance of two data-based cortical microcircuit templates", Journal of Physiology (Paris), vol. 103, no. 1-2, 2009. Abstract
Haeusler, S., and W. Maass, "A statistical analysis of information processing properties of lamina-specific cortical microcircuit models", Cerebral Cortex, vol. 17, no. 1, pp. 149-162, 2007. Abstract
Haeusler, S., H. Markram, and W. Maass, "Perspectives of the high dimensional dynamics of neural microcircuits from the point of view of low dimensional readouts", Complexity (Special Issue on Complex Adaptive Systems), vol. 8, no. 4, pp. 39-50, 2003. Abstract
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Jaeger, H., W. Maass, and J. Principe, "Introduction to the Special Issue on Echo State Networks and Liquid State Machines", Neural Networks, vol. 20, no. 3, pp. 287–289, 2007.
Joshi, P., and W. Maass, "Movement generation and control with generic neural microcircuits", BioADIT 2004, Lecture Notes in Computer Science, Lausanne, Springer, 2004. Abstract
Joshi, P., and W. Maass, "Movement generation with circuits of spiking neurons", Neural Computation, vol. 17, no. 8, pp. 1715-1738, 2005. Abstract
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Kaske, A., and W. Maass, "A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models", Neural Networks, vol. 19, no. 5, pp. 600-609, 2006. Abstract
Klampfl, S., R. Legenstein, and W. Maass, "Spiking neurons can learn to solve information bottleneck problems and to extract independent components", Neural Computation, vol. 21, no. 4, pp. 911-959, 2009. Abstract
Klampfl, S., and W. Maass, "Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks", NIPS 2009: Advances in Neural Information Processing Systems, vol. 22: MIT Press, 2010, 2009. Abstract
Klampfl, S., R. Legenstein, and W. Maass, "Information bottleneck optimization and independent component extraction with spiking neurons", NIPS 2006: Advances in Neural Information Processing Systems, vol. 19: MIT Press, pp. 713-720, 2007, 2006. Abstract
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Legenstein, R., and W. Maass, "What makes a dynamical system computationally powerful?", New Directions in Statistical Signal Processing: From System to Brains: MIT Press, pp. 127-154, 2007. Abstract
Legenstein, R., H. Markram, and W. Maass, "Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons", Reviews in the Neurosciences (Special Issue on Neuroinformatics of Neural and Artificial Computation), vol. 14, no. 1-2, pp. 5-19, 2003. Abstract
Legenstein, R., and W. Maass, "Edge of chaos and prediction of computational performance for neural microcircuit models", Neural Networks, vol. 20, no. 3, pp. 323-334, 2007. Abstract
Legenstein, R., D. Pecevski, and W. Maass, "A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback", PLoS Computational Biology, vol. 4, no. 10, pp. 1-27, 2008. Abstract
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Maass, W., "Computing with spikes", Special Issue on Foundations of Information Processing of Telematik, vol. 8, no. 1, pp. 32-36, 2002.
Maass, W., "Motivation, theory, and applications of liquid state machines", Computability in Context: Computation and Logic in the Real World: Imperial College Press, 2011. Abstract
Maass, W., T. Natschlaeger, and H. Markram, "A model for real-time computation in generic neural microcircuits", NIPS 2002: Advances in Neural Information Processing Systems, vol. 15: MIT Press, pp. 213–220, 2003, 2002. Abstract
Maass, W., P. Joshi, and E. D. Sontag, "Computational aspects of feedback in neural circuits", PLoS Computational Biology, vol. 3, no. 1, pp. 1-20, 2007. Abstract
Maass, W., R. Legenstein, and H. Markram, "A new approach towards vision suggested by biologically realistic neural microcircuit models", Biologically Motivated Computer Vision BMCV 2002, vol. 2525: Springer, pp. 282-293, 2002. Abstract
Maass, W., "Liquid Computing", Computability in Europe 2007 - CiE'07: Springer (Berlin), 2007. Abstract
Maass, W., T. Natschlaeger, and H. Markram, "Fading memory and kernel properties of generic cortical microcircuit models", Journal of Physiology (Paris), vol. 98, no. 4-6, pp. 315-330, 2004. Abstract
Maass, W., T. Natschläger, and H. Markram, "Computational models for generic cortical microcircuits", Computational Neuroscience: A Comprehensive Approach: CRC-Press, 2004. Abstract
Maass, W., and H. Markram, "Temporal integration in recurrent microcircuits", The Handbook of Brain Theory and Neural Networks, 2nd Edition: MIT Press, pp. 1159-1163, 2003.