Peer Reviewed Papers
In Press
Schummers, J Cronin, B , Wimmer, K, Stimberg, M , Martin, R, Obermayer, K , Kording, K and Sur, M (in press) Dynamics of orientation tuning in cat V1 neurons depend on location within layers and orientation maps, Frontiers in Neuroscience
2007
Kording KP (2007) Decision theory: what should the nervous system do? , Review, science free pdf on publishers site
Kording, KP, Beierholm, U., Ma, W., Quartz, S., Tenenbaum, J., Shams, L., (2007) Causal Inference in Cue Combination, PLOSOne 2(9): e943. doi:10.1371/journal.pone.0000943[pdf]
Kouml;rding KP, Tenenbaum JB, and Shadmehr R (2007) The dynamics of memory as a consequence of optimal adaptation to a changing body. Nature Neuroscience, 10:779-786 pdf of presubmission paper [News in spanish], [News in portugese], [News] Link to publishers page
2006
Kording, K., Tenenbaum, J. B., and Shadmehr, R. Multiple timescales and uncertainty in motor adaptation. (in press, 2006). Advances in Neural Information Processing Systems 19.
Kording, K. and Tenenbaum, J. B. Causal inference in sensorimotor integration. (2006). Advances in Neural Information Processing Systems 19. [pdf]
Kording and Wolpert, D. (2006) Bayesian decision theory in sensorimotor control. Trends in Cognitive Sciences (TICS) 10(7) 320-326 [pdf]
Purver, M., Kording, K. P., Griffiths, T. L., & Tenenbaum, J. B. (2006) Unsupervised topic modelling for multi-party spoken discourse. Proceedings of Coling/ACL 2006.[pdf]
2004
Kording, KP, Ku, SP and Wolpert, D. (2004) Bayesian Integration in force estimation J Neurophysiol 92(5):3161-5 [pdf]
Hafner, VV. , Fend, M. , König, P. and Körding, KP. (2004) Neural Information Processing Letters and Reviews, Predicting Properties of the Rat Somatosensory System by Sparse Coding [pdf]
Körding, KP., Fukunaga, I., Howard, IS., Ingram, J. and Wolpert, D. (2004) A neuroeconomics approach to measuring human loss functions, PLOS Biology, Vol. 2, No. 10, e330 doi:10.1371/journal.pbio.0020330 [pdf] [News auf Deutsch]
Körding, KP. and Wolpert, D. (2004) The loss function of sensorimotor learning, Proceedings of the National Academy of Sciences 101:9839-42 [pdf]
Körding, KP. and Wolpert, D. (2004) Bayesian Integration in Sensorimotor Learning, Nature 427:244-247 [pdf]
[New York times, News]
Körding, KP, Kayser, C., Einhäuser, W. and König,P., How are complex cell properties adapted to the statistics of natural scenes? Journal of Neurophysiology 91(1):206-212[pdf]
Körding, KP. and Wolpert, D. (2003) Bayesian Integration with Multimodal priors, NIPS [pdf]
Betsch, B, Einhäuser, W., Körding, KP and König, P. (2003) Biological Cybernetics, in press
2003
Hafner, V. V., Fend, M., Lungarella, M., Pfeifer, R., König, P., Körding, K. P. (2003), Optimal coding for naturally occurring whisker deflections, Proceedings of the Joint International Conference on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP), Springer Lecture Notes in Computer Science, pp. 805-812, ISSN 0302-9743, ISBN 3-540-40409-2, Istanbul
Einhäuser, W., Kayser, C., Körding, K.P. and König,P. (2003) Learning distinct and complementary feature-selectivities from natural colour videos. Reviews in the Neurosciences 14, p. 43-52, 2003. [pdf]
Klein, D.J., König, P. and Körding, K.P. (2003) Sparse spectrotemporal coding of sounds. EURASIP Journal of Applied Signal Processing, [pdf]
Körding, K.P., Kayser, C. and König, P. (2003) On the choice of a sparse prior, Reviews in the Neurosciences 14, p. 53-62, 2003
Kayser C, Körding KP, König P. (2003). Learning the nonlinearity of neurons from natural visual stimuli. Neural Computation. 15(8) 1751-1759. [pdf]
2002
Einhäuser,W. Kayser,C. Körding K.P. and König,P. Learning Multiple Feature Representations from Natural Image Sequences Artificial Neural Networks - ICANN 2002, Springer Verlag Berlin Heidelberg New York. [pdf]
Einhäuser, W., Kayser, C. , König, P. and Körding, K.P., Learning the invariance properties of complex cells from natural stimuli. (Eur J Neurosci 2002 Feb;15(3):475-86) [pdf]
Konrad P. Körding, Peter König, and David J. Klein (2002) Learning of sparse auditory receptive fields (IJCNN) [pdf]
2001
Körding, K.P., Kayser C., Betsch, B. and König, P., (2001) Non contact eye-tracking on cats. (J Neurosci Methods. Sep 30;110:103-111) [pdf]
Körding, K.P. and König, P., (2001) A spike based learning rule for the generation of invariant representations. ,Journal of Physiology Paris 94:539-548[pdf]
Körding, K.P. and König,P., (2001) Neurons with two sites of synaptic integration learn invariant representations. (Neural Computation 13:2823-2849) [pdf]
Kayser, C., Einhäuser, W., Dümmer, O., König, P. and Körding, K.P., (2001) Extracting slow subspaces from natural videos leads to complex cells. (International conference on artificial neural networks) [pdf]
Körding, K.P. and König ,P. , (2001) Supervised and unsupervised learning with two sites of synaptic integration. (Journal of Computational Neuroscience11:207-215) [pdf]
2000
Körding, K.P. and König, P., (2000) Two sites of synaptic integration: Relevant for learning (International Joint Conference on Neural Networks ) [pdf]
Körding, K.P. and König,P.,(2000) A learning rule for local decorrelation and dynamic recruitement (Neural Networks 13:1-9) [pdf]
Siegel,M. Körding,K.P. and König, P. (2000) Integrating top-down and bottom-up sensory processing by somato-dendritic interatctions (J. Comp. Neurosci 8:161-173)[pdf]
Konrad P. Körding and Peter König, (2000) Learning with two sites of synaptic integration (Network: Computation in Neural Systems 11:25-39) [pdf]
Under Revision
The motor cortical representation of the hand is adapted to the statistics of natural hand movements
Statistics of sensorimotor tasks predicts motor errors
Miscellaneous
Radioplay 45 min in German Language. "Reparatur". Christine Abbt, Doris Agotai, Jeanette Behringer, Silvia Berger, Konrad Paul Körding, Celina Ramjoue, Kaspar Schatzmann, Jair Stern. Played at the "end-of-term" celebration of the Collegium Helveticum. Part of the year-book. Sent on radio LORA Munich on June 20th 2003 along with a live interview.
Chapter for the OCNC School
Chapter for Novartis jointly with Daniel Wolpert
Invited Talks
Kreuth, Germany, 2007, Decision theory: What "should" the nervous system do?
IPAM, UCLA 2007, Decision making in the motor system
IPAM, UCLA 2007, Causal inference in sensorimotor integration
Tuebingen, Germany 2007, Adaptation in the visuomotor system
Delmenhorst, Germany 2007, Introduction to decision theory
Shanghai, 2007, Normative models of motor Control: why do we move the way we do
NYU, 2006, Causal Inference in Cue Combination
Giessen, 2006, The dynamics of motor learning and memory are the result of optimal adaptation to a changing body
Northwestern, 2006
Cornell, 2006
Yale, 2006
Brown, 2006
Sant Feliu de Guixols, Spain,2005, Motor-economics: the economics of forces, errors and goals
Paris, 2005, Calcul bayesien dans le systeme sensorimoteur
University of Chicago, 2005, Motor control as a decision problem
Johns Hopkins, 2005, Probabilities and Utilities: deciding how to move
Cosyne Workshop, 2005, Bayesian Methods in Sensory and Motor processing
Harvard, 2005, Motor economics: deciding how to move
Berkeley, 2005, Motor economics: deciding how to move
Cornell, 2004, Optimal processing in sensorimotor integration
Institute for cognitive research Osnabrück, 2004, What is optimal in sensorimotor integration
Functional Imaging Lab, London, 2004, Optimal statistical processing in the sensorimotor system
Nijmegen institute for cognition and information, 2004, Probabilistic processing in sensorimotor integration
Neurovision meeting Bochum, 2004, Bayesian Processing in the human sensorimotor system
MIT, Cambridge, 2004, Optimality criteria for visual representations and sensorimotor integration
Cold Spring Harbour Labs, 2004, Towards a Bayesian Nose
Brain and Mind Institute Lausanne, 2003, Optimality in visual representations and sensorimotor integration
Institute of Theoretical Biology Berlin, 2003, Bayesian integration in sensorimotor learning
GATSBY, London, 2003, The sensorimotor system uses the Bayes rule
Cambridge, 2003, Bayesian integration in the sensorimotor system
Plymouth, 2003,Learning from the real world - one algorithm for visual and auditory stimuli.
Oldenburg, 2003,Sparse Coding of speech data predicts properties of the auditory system
GATSBY, London, 2003, Learning hierarchical representations from videos of natural scenes
Center for Neuroscience, Davis CA, 2002, Complex Cells, A question of time
Asilomar, 2002, Complex Cells, optimality to natural scenes
Wolpert Lab 2002, Optimality of Complex Cells
Thesis Defense, Zuerich, 2001, Optimality and Learning, From Microscopic cell properties to natural scenes
Seung Lab MIT, 2000, Learning Invariant Representations
Brown University, 2000, Invariant Representations and the Binding Problem
Cold Spring Harbor Lab , 2000, Complex Cells emerge from natural Videos
Banbury Meeting : Statistics of Natural Scenes , 2000, What cats see and what networks can learn from this
Heidelberg Max Planck Institute for Medical Research, 2000, The significance of two sites of synaptic integration
GATSBY and University College London, 2000, Physiologically realistic mechanisms for learning
ITB Berlin,1999, Significance of two sites of synaptic integration
