Publications

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1995
Dominey, P. F., M. Arbib, and J-P. Joseph, "A model of corticostriatal plasticity for learning oculomotor associations and sequences", Journal of Cognitive Neuroscience, vol. 7, no. 3, pp. 311-336, 1995. Abstract  Download: dominey1995jocn.pdf (1.09 MB)
Dominey, P. F., "Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning", Biological Cybernetics, vol. 73, no. 3, pp. 265-74, 08/1995.  Download: dominey1995biocyber.pdf (996.6 KB)
1997
Dominey, P. F., "An anatomically structured sensory-motor sequence learning system displays some general linguistic capacities.", Brain and Language, vol. 59, no. 1, pp. 50-75, 1997. Abstract  Download: dominey1997brainlang.pdf (198.49 KB)
Dominey, P. F., and M. Jeannerod, "Contribution of frontostriatal function to sequence learning in Parkinson's disease: evidence for dissociable systems", NeuroReport, vol. 8, no. 5, pp. iii-ix, 03/1997. Abstract  Download: dominey 97 neuroreport.pdf (214.39 KB)
Dominey, P. F., and D. Boussaoud, "Encoding behavioral context in recurrent networks of the fronto-striatal system: a simulation study", Cognitive Brain Research Volume 6, Issue 1, July 1997, Pages , vol. 6, no. 1, pp. 53-65, 07/1997. Abstract  Download: dominey1997cogbrres.pdf (472 KB)
1998
Dominey, P. F., "Influences of temporal organization on sequence learning and transfer: Comments on Stadler (1995) and Curran and Keele (1993)", Journal of Experimental Psychology: Learning, Memory, and Cognition, vol. 24, no. 1, pp. 234-248, 01/1998. Abstract
Dominey, P. F., "A shared system for learning serial and temporal structure of sensori-motor sequences? Evidence from simulation and human experiments", Cognitive Brain Research, vol. 6, no. 3, pp. 163-172, 01/1998.  Download: dominey 98 cogn brain res.pdf (501.91 KB)
Dominey, P. F., T. Lelekov, J. Ventre-Dominey, and M. Jeannerod, "Dissociable processes for learning the surface structure and abstract structure of sensorimotor sequences", Journal of Cognitive Neuroscience, vol. 10, no. 6, pp. 734-51, 11/1998.  Download: dominey1998jocn.pdf (372.63 KB)
2000
Dominey, P. F., and F. Ramus, "Neural network processing of natural language: I. Sensitivity to serial, temporal and abstract structure of language in the infant", Language and Cognitive Processes, vol. 15, no. 1, pp. 87-127, 2000.  Download: LCP00.PDF (481 KB)
Atiya, A. F., and A. G. Parlos, "New Results on Recurrent Network Training: unifying the Algorithms and Accelerating Convergence", IEEE Transactions on Neural Networks, vol. 11, no. 3, pp. 697–709, 2000.
2001
Jaeger, H., "Short term memory in echo state networks", GMD Report 152: German National Research Center for Information Technology, 2001.
Jaeger, H., "The ``echo state'' approach to analysing and training recurrent neural networks - with an Erratum note", GMD Report 148: German National Research Center for Information Technology, 2001.
2002
Natschläger, T., W. Maass, and H. Markram, "The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series", Special Issue on Foundations of Information Processing of {TELEMATIK}, vol. 8, no. 1, pp. 39–43, 2002. Abstract
Natschläger, T., H. Markram, and W. Maass, "Computer models and analysis tools for neural microcircuits", A Practical Guide to Neuroscience Databases and Associated Tools: Kluver Academic Publishers (Boston), 2002.
Maass, W., "Computing with spikes", Special Issue on Foundations of Information Processing of Telematik, vol. 8, no. 1, pp. 32-36, 2002.
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., "On the computational power of neural microcircuit models: Pointers to the literature", International Conference on Artificial Neural Networks - ICANN 2002, vol. 2415: Springer, pp. 254-256, 2002.
Maass, W., T. Natschlaeger, and H. Markram, "Real-time Computing without stable states: A New Framework for Neural Computation Based on Perturbations", Neural Computation, vol. 14, no. 11, pp. 2531–2560, 2002. Abstract
Jaeger, H., "Tutorial on training recurrent neural networks, covering {BPTT}, {RTRL}, {EKF} and the ``echo state network'' approach", GMD Report 159: German National Research Center for Information Technology, pp. 48 pp., 2002.
Jaeger, H., "Adaptive nonlinear system identification with echo state networks", In: Advances in Neural Information Processing Systems: MIT Press, Cambridge, MA, , pp. 593-600, 2003, 2002.
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
2003
Jaeger, H., Advances in Neural Information Processing Systems 15, : MIT Press Cambridge, MA, pp. 593–600, 2003.
Fernando, C., and S. Sojakka, "Pattern recognition in a bucket", Proceedings of the 7th European Conference on Artificial Life, pp. 588–597, 2003.
Natschlaeger, T., H. Markram, and W. Maass, "Computer Models and analysis tools for neural microcircuits", Neuroscience Databases. A Practical Guide, Boston, Kluwer Academic Publishers, pp. 123-138, 2003. 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