Publications

2017

Krause, O., Glasmachers, T., & Igel, C. (2017). Qualitative and Quantitative Assessment of Step Size Adaptation Rules. In Conference on Foundations of Genetic Algorithms (FOGA). ACM.
Richter, M., Lins, J., & Schöner, G. (2017). A neural dynamic model generates descriptions of object-oriented actions. Topics in Cognitive Science, 9(1), 35–47. http://doi.org/10.1111/tops.12240
2016

Doğan, Ü., Glasmachers, T., & Igel, C. (2016). A Unified View on Multi-class Support Vector Classification. Journal of Machine Learning Research, 17(45), 1–32.
Escalante-B., A. N., & Wiskott, L. (2016). Theoretical analysis of the optimal free responses of graph-based SFA for the design of training graphs. Journal of Machine Learning Research, 17(157), 1–36. Retrieved from http://jmlr.org/papers/v17/15-311.html
Escalante-B., A. N., & Wiskott, L. (2016, January). Improved graph-based SFA: Information preservation complements the slowness principle. e-print arXiv:1601.03945. Retrieved from http://arxiv.org/abs/1601.03945
Glasmachers, T. (2016). Finite Sum Acceleration vs. Adaptive Learning Rates for the Training of Kernel Machines on a Budget. In NIPS workshop on Optimization for Machine Learning.
Glasmachers, T. (2016). Small Stochastic Average Gradient Steps. In NIPS workshop on Optimizing the Optimizers.
Krause, O., Glasmachers, T., Hansen, N., & Igel, C. (2016). Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Krause, O., Glasmachers, T., & Igel, C. (2016). Multi-objective Optimization with Unbounded Solution Sets. In NIPS workshop on Bayesian Optimization.
Loshchilov, I., & Glasmachers, T. (2016). Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES). In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Melchior, J., Fischer, A., & Wiskott, L. (2016). How to Center Deep Boltzmann Machines. Journal of Machine Learning Research, 17(99), 1–61. Retrieved from http://jmlr.org/papers/v17/14-237.html
Michael, M., Feist, C., Schuller, F., & Tschentscher, M. (2016). Fast Change Detection for Camera-based Surveillance Systems. In Proceedings of the IEEE International Conference on Intelligent Transportation Systems (Vol. 19, pp. 1–8).
Rekauzke, S., Nortmann, N., Staadt, R., Hock, H. S., Schöner, G., & Jancke, D. (2016). Temporal asymmetry in dark-bright processing initiates propagating activity across primary visual cortex. J Neurosci, 36(6), 1902–1913.
Spoida, K., Eickelbeck, D., Karapinar, R., Eckhardt, T., Mark, M. D., Jancke, D., et al. (2016). Melanopsin variants as intrinsic optogenetic On and Off switches for transient versus sustained activation of G protein pathways. Curr Biol., 26(9), 1206–1212.
Tekülve, J., Zibner, S. K. U., & Schöner, G. (2016). A neural process model of learning to sequentially organize and activate pre-reaches. In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2016 Joint IEEE International Conferences on.
Tomforde, S., Rudolph, S., Bellman, K., & Würtz, R. P. (2016). "Self-Improving System Integration" – Preface for the SISSY′16 Workshop. In Proc. ICAC (p. 275). http://doi.org/10.1109/ICAC.2016.74
Tomforde, S., Rudolph, S., Bellman, K., & Würtz, R. P. (2016). An Organic Computing Perspective on Self-Improving System Interweaving at Runtime. In Proc. ICAC (pp. 276–284). http://doi.org/10.1109/ICAC.2016.15
Weghenkel, B., Fischer, A., & Wiskott, L. (2016). Graph-based Predictable Feature Analysis. arXiv:1602.00554v1. Retrieved from http://arxiv.org/abs/1602.00554v1
Weihs, C., & Glasmachers, T. (2016). Supervised Classification. In C. Weihs, Jannach, D., Vatolkin, I., & Rudolph, G. (Eds.), Music Data Analysis: Foundations and Applications.
2015

Fahmy, G., Alqallaf, A., & Wurtz, R. (2015). Phase based detection of JPEG counter forensics. In 2015 IEEE International Conference on Electronics, Circuits, and Systems (ICECS) (pp. 37–40). http://doi.org/10.1109/ICECS.2015.7440243
Bodenstein, C., Tremer, M., Overhoff, J., & Würtz, R. P. (2015). A smartphone-controlled autonomous robot. In Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery, Zhangjiajie, China, Aug. 15-17 (pp. 2360–2367). http://doi.org/10.1109/FSKD.2015.7382314
Dinse, H. R., & Tegenthoff, M. (2015). Evoking plasticity through sensory stimulation: Implications for learning and rehabilitation . e-Neuroforum, 1(1), .
Escalante-B., A. N., & Wiskott, L. (2015). Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs. e-print arXiv:1509.08329. Retrieved from http://arxiv.org/abs/1509.08329
Günther, M., Böhringer, S., Wieczorek, D., & Würtz, R. P. (2015). Reconstruction of Images from Gabor Graphs with Applications in Facial Image Processing. International Journal of Wavelets, Multiresolution and Information Processing, 13(4), 1550019-1–25. http://doi.org/10.1142/S0219691315500198
Haag, L. M., Heba, S., Lenz, M., Glaubitz, B., Höffken, O., Kalisch, T., et al. (2015). Resting BOLD fluctuations in the primary somatosensory cortex correlate with tactile acuity. Cortex, 64, 20–28.
Horn, D., & Brüggenthies, M. (2015). Video-based Parking Space Detection: Localisation of Vehicles and Development of an Infrastructure for a Routeing System. In Proceedings of the Forum Bauinformatik (pp. 175–182).
Ibisch, A., Houben, S., Michael, M., Kesten, R., & Schuller, F. (2015). Arbitrary object localization and tracking via multiple-camera surveillance system embedded in a parking garage. In Proceedings of the SPIE (p. 94070G-94070G-12).
Kompella, V. R., Stollenga, M., Luciw, M., & Schmidhuber, J. (2015). Continual curiosity-driven skill acquisition from high-dimensional video inputs for humanoid robots. Artificial Intelligence.
Kosilek, R. P., Frohner, R., Würtz, R. P., Berr, C. M., Schopohl, J., Reincke, M., & Schneider, H. J. (2015). Automatic face classification in Cushing′s syndrome and acromegaly: Review, current results and future perspectives. European Journal of Endocrinology, 173(4), M39–M44. http://doi.org/10.1530/EJE-15-0429
Krause, O., & Glasmachers, T. (2015). A CMA-ES with Multiplicative Covariance Matrix Updates. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Mattos, D., Schöner, G., Zatsiorsky, V. M., & Latash, M. L. (2015). Motor equivalence during multi-finger accurate force production. Experimental Brain Research, 233, 487–502. http://doi.org/10.1007/s00221-014-4128-1
Michael, M., & Schlipsing, M. (2015). Extending Traffic Light Recognition: Efficient Classification of Phase and Pictogram. In Proceedings of the IEEE International Joint Conference on Neural Networks.
Neher, T., Cheng, S., & Wiskott, L. (2015). Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics. PLoS Comput Biol, 11, e1004250. http://doi.org/10.1371/journal.pcbi.1004250
Nortmann, N., Rekauzke, S., Azimi, Z., Onat, S., König, P., & Jancke, D. (2015). Visual homeostatic processing in V1: When probability meets dynamics . Frontiers in Systems Neuroscience , 9.
Nortmann, N., Rekauzke, S., Onat, S., König, P., & Jancke, D. (2015). Primary Visual Cortex Represents the Difference Between Past and Present. Cerebral Cortex, 25(6), 1427–1440.
Reimann, H., Lins, J., & Schöner, G. (2015). The Dynamics of Neural Activation Variables. Paladyn, Journal of Behavioral Robotics, 6(1), 57–70.
Richthofer, S., & Wiskott, L. (2015). Predictable Feature Analysis. In Workshop New Challenges in Neural Computation 2015 (NC2) (pp. 68–75). Retrieved from https://www.techfak.uni-bielefeld.de/ fschleif/mlr/mlr_03_2015.pdf
Richthofer, S., & Wiskott, L. (2015). Predictable Feature Analysis. In 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) (pp. 190–196). http://doi.org/10.1109/ICMLA.2015.158
Ritter, P., Born, J., Brecht, M., Dinse, H. R., Heinemann, U., Pleger, B., et al. (2015). State-dependencies of learning across brain scales. Frontiers in Computational Neuroscience, 9.
Sandamirskaya, Y., & Storck, T. (2015). Artificial Neural Networks — Methods and Applications in Bio-/Neuroinformatics. In P. Koprinkova-Hristova, Mladenov, V., & Kasabov, N. K. (Eds.) (Vol. 4). Springer.
Schoenfeld, F., & Wiskott, L. (2015). Modeling place field activity with hierarchical slow feature analysis. Frontiers in Computational Neuroscience, 9(51). http://doi.org/10.3389/fncom.2015.00051
Schönfeld, F., & Wiskott, L. (2015). Modeling place field activity with hierarchical slow feature analysis. frontiers in Computational Neuroscience, 9(51). http://doi.org/10.3389/fncom.2015.00051
Tschentscher, M., Koch, C., König, M., Salmen, J., & Schlipsing, M. (2015). Scalable real-time parking lot classification: An evaluation of image features and supervised learning algorithms. In Proceedings of the IEEE International Joint Conference on Neural Networks.
Zibner, S. K. U., Tekülve, J., & Schöner, G. (2015). The Neural Dynamics of Goal-Directed Arm Movements: A Developmental Perspective. In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2015 Joint IEEE International Conferences on (pp. 154–161).
Zibner, S. K. U., Tekülve, J., & Schöner, G. (2015). The Sequential Organization of Movement is Critical to the Development of Reaching: A Neural Dynamics Account. In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2015 Joint IEEE International Conferences on (pp. 39–46).
2014

Lomp, O., Terzić, K., Faubel, C., du Buf, J. M. H., & Schöner, G. (2014). Instance-based Object Recognition with Simultaneous Pose Estimation Using Keypoint Maps and Neural Dynamics. In S. Wermter, Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P. D., , S. M., et al. (Eds.), ICANN 2014 (Vol. 8681, pp. 451–458). Hamburg.
Muret, D., Dinse, H. R., Macchione, S., Urquizar, C., Farne, A., & Reilly, K. T. (2014). Touch improvement at the hand transfers to the face. Curr. Biol., 24(16), R736–737.
Balliu, B., Würtz, R. P., Horsthemke, B., Wieczorek, D., & Böhringer, S. (2014). Classification and visualization based on derived image features: application to genetic syndromes. PLOS One, 9(11), e109033. http://doi.org/10.1371/journal.pone.0109033
Bell, C., Storck, T., & Sandamirskaya, Y. (2014). Learning to Look: a Dynamic Neural Fields Architecture for Gaze Shift Generation. In International Conference for Artificial Neural Networks, ICANN. Hamburg, Germany.
Bellman, K., Tomforde, S., & Würtz, R. P. (2014). "Self-Improving System Integration" – Preface for the SISSY14 Workshop. In Proc. SASO, London (p. 122). IEEE.
Bellman, K., Tomforde, S., & Würtz, R. P. (2014). Interwoven Systems: Self-improving Systems Integration. In Proc. SASO, London (pp. 123–127). IEEE.
Bruns, P., Camargo, C. J., Campanella, H., Esteve, J., Dinse, H. R., & Röder, B. (2014). Tactile Acuity Charts: A Reliable Measure of Spatial Acuity. PloS one, 9(2), e87384.
Chavane, F., Sharon, D., Jancke, D., Marre, O., Fregnac, Y., & Grinvald, A. (2014). Optogenetic Assessment of Horizontal Interactions in Primary Visual Cortex (pg 4976, 2014). J Neurosci, 34(26), 8930–8930.
Dähne, S., Wilbert, N., & Wiskott, L. (2014). Slow Feature Analysis on Retinal Waves Leads to V1 Complex Cells. PLoS Comput Biol, 10(5), e1003564. http://doi.org/10.1371/journal.pcbi.1003564
Danafar, S., Rancoita, P. M. V., Glasmachers, T., Whittingstall, K., & Schmidhuber, J. (2014). Testing Hypotheses by Regularized Maximum Mean Discrepancy. International Journal of Computer and Information Technology (IJCIT), 3(2).
Glasmachers, T. (2014). Handling Sharp Ridges with Local Supremum Transformations. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Glasmachers, T. (2014). Optimized Approximation Sets for Low-dimensional Benchmark Pareto Fronts. In Parallel Problem Solving from Nature (PPSN). Springer.
Glasmachers, T., Naujoks, B., & Rudolph, G. (2014). Start Small, Grow Big - Saving Multiobjective Function Evaluations. In Parallel Problem Solving from Nature (PPSN). Springer.
Houben, S. (2014). Towards the intrinsic self-calibration of a vehicle-mounted omni-directional radially symmetric camera. In Proceedings of IEEE Intelligent Vehicles Symposium (pp. 878–883).
Ibisch, A., Houben, S., Schlipsing, M., Kesten, R., Reimche, P., Schuller, F., & Altinger, H. (2014). Towards highly automated driving in a parking garage: General object localization and tracking using an environment-embedded camera system. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 426–431).
Kattenstroth, J. C., Kalisch, T., Tegenthoff, M., & Dinse, H. R. (2014). Tanz im Alter: Fitness für Gehirn, Geist und Körper . In C. Behrens & Rosenberg, C. (Eds.), TanzZeit – LebensZeit, Tanzforschung 2014 (pp. 115–135). Leipzig: Henschel Verlag .
Knips, G., Zibner, S. K. U., Reimann, H., Popova, I., & Schöner, G. (2014). A neural dynamics architecture for grasping that integrates perception and movement generation and enables on-line updating. In International Conference on Intelligent Robots and Systems (IROS) (pp. 646–653).
Knips, G., Zibner, S. K. U., Reimann, H., Popova, I., & Schöner, G. (2014). Reaching and grasping novel objects: Using neural dynamics to integrate and organize scene and object perception with movement generation. In International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB) (pp. 416–423).
Kompella, V. R. (2014). Slow Feature Analysis for Curiosity-Driven Agents, 2014 IEEE WCCI Tutorial.
Kompella, V. R. (2014). Slowness Learning for Curiosity-Driven Agents. Doctoral thesis, Università della svizzera italiana (USI).
Kompella, V. R., Kazerounian, S., & Schmidhuber, J. (2014). An Anti-hebbian Learning Rule to Represent Drive Motivations for Reinforcement Learning. In From Animals to Animats 13 (pp. 176–187). Springer International Publishing.
Kompella, V. R., Stollenga, M. F., Luciw, M. D., & Schmidhuber, J. (2014). Explore to See, Learn to Perceive, Get the Actions for Free: SKILLABILITY. In Proceedings of IEEE Joint Conference of Neural Networks (IJCNN).
Kozyrev, V., Eysel, U. T., & Jancke, D. (2014). Voltage-sensitive dye imaging of transcranial magnetic stimulation-induced intracortical dynamics. Proceedings of the National Academy of Sciences, 111(37), 13553–13558.
Krause, T. U., Schrör, P. Y., & Würtz, R. P. (2014). Spiking network simulations. In B. Hammer, Martinetz, T., & Villmann, T. (Eds.), Proceedings of New Challenges in Neural Computation, Münster (pp. 14–15).
Ladda, A. M., Pfannmoeller, J. P., Kalisch, T., Roschka, S., Platz, T., Dinse, H. R., & Lotze, M. (2014). Effects of combining 2 weeks of passive sensory stimulation with active hand motor training in healthy adults. PloS one, 9(1), e84402.
Lessmann, M., & Würtz, R. P. (2014). Learning of invariant object recognition in a hierarchical network. Neural Networks, 54, 70–84. http://doi.org/10.1016/j.neunet.2014.02.011
Lessmann, M., & Würtz, R. P. (2014). Online Learning of Invariant Object Recognition in a Hierarchical Neural Network. In S. Wermter, Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., et al. (Eds.), Proc. ICANN (pp. 427–434). Springer.
Lins, J., & Schöner, G. (2014). Neural Fields. In S. Coombes, beim Graben, P., Potthast, R., & , J. W. (Eds.) (pp. 319–339). Springer Berlin Heidelberg.
Lissek, S., Vallana, G. S., Schlaffke, L., Lenz, M., Dinse, H. R., & Tegenthoff, M. (2014). Opposing effects of dopamine antagonism in a motor sequence task—tiapride increases cortical excitability and impairs motor learning. Frontiers in behavioral neuroscience, 8.
Luciw, M., Kazerounian, S., Sandamirskaya, Y., Schöner, G., & Schmidhuber, J. (2014). Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics. In Simulation of Adaptive Behavior, SAB.
Maruyama, S., Dineva, E., Spencer, J. P., & Schöner, G. (2014). Change occurs when body meets environment: A review of the embodied nature of development. Japanese Psychological Research, 56, 385–401. http://doi.org/10.1111/jpr.12065
Norman, J., Hock, H., & Schoner, G. (2014). Contrasting accounts of direction and shape perception in short-range motion: Counterchange compared with motion energy detection. Attention, perception & psychophysics, 76, 1350–70. http://doi.org/10.3758/s13414-014-0650-2
Richter, M., Lins, J., Schneegans, S., Sandamirskaya, Y., & Schöner, G. (2014). Autonomous Neural Dynamics to Test Hypotheses in a Model of Spatial Language. In P. Bello, Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 2847–2852). Austin, TX: Cognitive Science Society.
Richter, M., Lins, J., Schneegans, S., & Schöner, G. (2014). A neural dynamic architecture resolves phrases about spatial relations in visual scenes. In 24th International Conference on Artificial Neural Networks (ICANN) (pp. 201–208). Heidelberg, Germany: Springer.
Sandamirskaya, Y., & Storck, T. (2014). Neural-Dynamic Architecture for Looking: Shift from Visual to Motor Target Representation for Memory Saccade. In IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2014).
Schlipsing, M. (2014). Videobasierte Leistungserfassung im Fußball. Doctoral thesis, Ruhr-Universität Bochum.
Schlipsing, M., Salmen, J., Tschentscher, M., & Igel, C. (2014). Adaptive pattern recognition in real-time video-based soccer analysis. Journal of Real-Time Image Processing, 1–17.
Schneegans, S., Spencer, J. P., Schöner, G., Hwang, S., & Hollingworth, A. (2014). Dynamic interactions between visual working memory and saccade target selection. Journal of vision, 14(11), 9.
Sczesny-Kaiser, M., Bauknecht, A., Höffken, O., Tegenthoff, M., Dinse, H. R., Jancke, D., et al. (2014). Synergistic effects of noradrenergic modulation with atomoxetine and 10 Hz repetitive transcranial magnetic stimulation on motor learning in healthy humans. BMC neuroscience, 15(1), 46.
Sczesny-Kaiser, M., Bauknecht, A., Hoffken, O., Tegenthoff, M., Dinse, H. R., Jancke, D., et al. (2014). Synergistic effects of noradrenergic modulation with atomoxetine and 10 Hz repetitive transcranial magnetic stimulation on motor learning in healthy humans. BMC Neurosci, 15, 46.
Sigala, R., Haufe, S., Roy, D., Dinse, H. R., & Ritter, P. (2014). The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models. Front Comput Neurosci, 8, 36.
Sprekeler, H., Zito, T., & Wiskott, L. (2014). An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation. Journal of Machine Learning Research, 15, 921–947. Retrieved from http://jmlr.org/papers/v15/sprekeler14a.html
Strub, C., Wörgötter, F., Ritter, H., & Sandamirskaya, Y. (2014). Correcting Pose Estimates during Tactile Exploration of Object Shape: a Neuro-robotic Study. In Development and Learning and Epirobotics (ICDL-Epirob), IEEE International Conference on.
Strub, C., Wörgötter, F., Ritter, H., & Sandamirskaya, Y. (2014). Using Haptics to Extract Object Shape from Rotational Manipulations. In Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on. IEEE.
Wang, N. (2014). Learning natural image statistics with variants of restricted Boltzmann machines. Doctoral thesis, International Graduate School of Neuroscience, Ruhr-Universität Bochum.
Wang, N., Jancke, D., & Wiskott, L. (2014). Modeling correlations in spontaneous activity of visual cortex with Gaussian-binary deep Boltzmann machines. In Proc. Bernstein Conference for Computational Neuroscience, Sep 3–5,Göttingen, Germany (pp. 263–264). BFNT Göttingen.
Wang, N., Jancke, D., & Wiskott, L. (2014). Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines. In Proc. International Conference of Learning Representations (ICLR′14, workshop), Apr 14–16,Banff, Alberta, Canada.
Wang, N., Melchior, J., & Wiskott, L. (2014). Gaussian-binary Restricted Boltzmann Machines on Modeling Natural Image statistics (Vol. 1401.5900). arXiv.org e-Print archive. Retrieved from http://arxiv.org/abs/1401.5900
Weghenkel, B., & Wiskott, L. (2014). Learning predictive partitions for continuous feature spaces. In Proc. 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Apr 23-25, Bruges, Belgium (pp. 577–582).
Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., & Schmidhuber, J. (2014). Natural Evolution Strategies. Journal of Machine Learning Research, 15, 949–980.
Wiskott, L., Würtz, R. P., & Westphal, G. (2014). Elastic Bunch Graph Matching. Scholarpedia, 9, 10587. http://doi.org/10.4249/scholarpedia.10587
Zhang, S., Schoenfeld, F., Wiskott, L., & Manahan-Vaughan, D. (2014). Spatial representations of place cells in darkness are supported by path integration and border information. Frontiers in Behavioral Neuroscience, 8(222). http://doi.org/10.3389/fnbeh.2014.00222
2013

Kattenstroth, J. C., Kalisch, T., Kowalewski, R., Tegenthoff, M., & Dinse, H. R. (2013). Quantitative assessment of joint position sense recovery in subacute stroke patients: a pilot study. J Rehabil Med, 45(10), 1004–1009.
Hickmott, P., & Dinse, H. (2013). Effects of aging on properties of the local circuit in rat primary somatosensory cortex (S1) in vitro. Cereb. Cortex, 23(10), 2500–2513.
Hickmott, P., & Dinse, H. (2013). Effects of aging on properties of the local circuit in rat primary somatosensory cortex (S1) in vitro. Cereb. Cortex, 23(10), 2500–2513.
Beste, C., & Dinse, H. R. (2013). Learning without training. Curr. Biol., 23(11), R489–499.
Gatica Tossi, M. A., Lillemeier, A. S., & Dinse, H. R. (2013). Influence of stimulation intensity on paired-pulse suppression of human median nerve somatosensory evoked potentials. Neuroreport, 24(9), 451–456.
Hoffken, O., Lenz, M., Sczesny-Kaiser, M., Dinse, H. R., & Tegenthoff, M. (2013). Phosphene thresholds correlate with paired-pulse suppression of visually evoked potentials. Brain Stimul, 6(2), 118–121.
Freyer, F., Becker, R., Dinse, H. R., & Ritter, P. (2013). State-dependent perceptual learning. J. Neurosci., 33(7), 2900–2907.
Azizi, A. H., Wiskott, L., & Cheng, S. (2013). A computational model for preplay in the hippocampus. Frontiers in Computational Neuroscience, 7(161), 1–15. http://doi.org/10.3389/fncom.2013.00161
Caup, L., Salmen, J., Muharemovic, I., & Houben, S. (2013). Video-Based Trailer Articulation Estimation. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 1179–1184).
Escalante-B., A. -N., & Wiskott, L. (2013). How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis. Cognitive Sciences EPrint Archive (CogPrints). Retrieved from http://cogprints.org/8966/
Escalante-B., A. N., & Wiskott, L. (2013). How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis. Journal of Machine Learning Research, 14, 3683–3719. Retrieved from http://jmlr.org/papers/v14/escalante13a.html
Frohner, R., Würtz, R. P., Kosilek, R. P., & Schneider, H. J. (2013). Optimierung der Gesichtsklassifikation bei der Erkennung von Akromegalie. Austrian Journal of Clinical Endocrinology and Metabolism, 6(3), 20–24.
Glasmachers, T. (2013). A Natural Evolution Strategy with Asynchronous Strategy Updates. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Glasmachers, T. (2013). The Planning-ahead SMO Algorithm (No. arxiv:1305.0423v1). arxiv.org.
Glasmachers, T., & Doğan, Ü. (2013). Accelerated Coordinate Descent with Adaptive Coordinate Frequencies. In Proceedings of the fifth Asian Conference on Machine Learning (ACML).
Houben, S., Komar, M., A. Hohm,, Lüke, S., Neuhausen, M., & Schlipsing, M. (2013). On-Vehicle Video-Based Parking Lot Recognition with Fisheye Optics. In Proceedings of the IEEE Annual Conference on Intelligent Transportation Systems (pp. 7–12).
Houben, S., Stallkamp, J., Salmen, J., Schlipsing, M., & Igel, C. (2013). Detection of Traffic Signs in Real-World Images: The German Traffic Sign Detection Benchmark. In Proceedings of the International Joint Conference on Neural Networks.
Ibisch, A., Stümper, S., Altinger, H., Neuhausen, M., Tschentscher, M., Schlipsing, M., et al. (2013). Autonomous Driving in a Parking Garage: Vehicle Localization and Tracking Using Environment-embedded LIDAR Sensors. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 829–934).
Kattenstroth, J. C., Kalisch, T., Holt, S., Tegenthoff, M., & Dinse, H. R. (2013). Six months of dance intervention enhances postural, sensorimotor, and cognitive performance in elderly without affecting cardio-respiratory functions. Front Aging Neurosci, 5, 5.
Kazerounian, S., Luciw, M., Richter, M., & Sandamirskaya, Y. (2013). Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics. In International Joint Conference on Neural Networks (IJCNN).
Kosilek, R. P., Schopohl, J., Grünke, M., Dimopoulou, C., Stalla, G. K., Lammert, A., et al. (2013). Automatic face classification of Cushing’s syndrome in women - A novel screening approach. Experimental and Clinical Endocrinology and Diabetes. http://doi.org/10.1055/s-0033-1349124
Krause, O., Fischer, A., Glasmachers, T., & Igel, C. (2013). Approximation properties of DBNs with binary hidden units and real-valued visible units. In Proceedings of the International Conference on Machine Learning (ICML).
Krüger, N., Janssen, P., Kalkan, S., Lappe, M., Leonardis, A., Piater, J., et al. (2013). Deep Hierarchies in the Primate Visual Cortex: What Can We Learn For Computer Vision? IEEE Trans. on Pattern Analysis and Machine Intelligence, 35(8), 1847–1871. http://doi.org/10.1109/TPAMI.2012.272
Lissek, S., Vallana, G. S., Gunturkun, O., Dinse, H., & Tegenthoff, M. (2013). Brain activation in motor sequence learning is related to the level of native cortical excitability. PLoS ONE, 8(4), e61863.
Lomp, O., Zibner, S. K. U., Richter, M., Ranó, I., & Schöner, G. (2013). A software framework for cognition, embodiment, dynamics, and autonomy in robotics: cedar. In Artificial Neural Networks and Machine Learning–ICANN 2013 (pp. 475–482). Springer.
Luciw, M., Kazerounian, S., Lakhmann, K., Richter, M., & Sandamirskaya, Y. (2013). Learning the Perceptual Conditions of Satisfaction of Elementary Behaviors. In Robotics: Science and Systems (RSS), Workshop "Active Learning in Robotics: Exploration, Curiosity, and Interaction".
Luciw*, M., Kompella*, V., Kazerounian, S., & Schmidhuber, J. (2013). An intrinsic value system for developing multiple invariant representations with incremental slowness learning. Frontiers in neurorobotics, 7, *Joint first authors.
Melchior, J., Fischer, A., Wang, N., & Wiskott, L. (2013). How to Center Binary Restricted Boltzmann Machines (Vol. 1311.1354). arXiv.org e-Print archive. Retrieved from http://arxiv.org/pdf/1311.1354.pdf
Michael, M., Salmen, J., Stallkamp, J., & Schlipsing, M. (2013). Real-Time Stereo Vision: Optimizing Semi-Global Matching. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 1197–1202).
Müller, M. K., Tremer, M., Bodenstein, C., & Würtz, R. P. (2013). Learning invariant face recognition from examples. Neural Networks, 41, 137–146. http://doi.org/10.1016/j.neunet.2012.07.006
Neher, T., Cheng, S., & Wiskott, L. (2013). Are memories really stored in the hippocampal CA3 region? BoNeuroMed.
Neher, T., Cheng, S., & Wiskott, L. (2013). Are memories really stored in the hippocampal CA3 region? In Proc. 10th Göttinger Meeting of the German Neuroscience Society, Mar 13-16, Göttingen, Germany (p. 104).
Onat, S., Jancke, D., & König, P. (2013). Cortical long-range interactions embed statistical knowledge of natural sensory input: a voltage-sensitive dye imaging study. F1000Research, 2.
Richthofer, S., & Wiskott, L. (2013). Predictable Feature Analysis. arXiv.org e-Print archive. Retrieved from http://arxiv.org/abs/1311.2503
Salmen, J. (2013). Eine Systemarchitektur für effiziente videobasierte Fahrerassistenzsysteme. Doctoral thesis, Ruhr-Universität Bochum.
Sandamirskaya, Y. (2013). Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures. Frontiers in Neuroscience, 7, 276.
Sandamirskaya, Y., & Conradt, J. (2013). Increasing Autonomy of Learning SensorimotorTransformations with Dynamic Neural Fields. In International Conference on Robotics and Automation (ICRA), Workshop "Autonomous Learning".
Sandamirskaya, Y., & Conradt, J. (2013). Learning Sensorimotor Transformations with Dynamic Neural Fields. In International Conference on Artificial Neural Networks (ICANN).
Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to Extend the Embodiment Stance toward Higher Cognition. New Ideas in Psychology, 31(3), 322–339.
Schlipsing, M., Salmen, J., & Igel, C. (2013). Echtzeit-Videoanalyse im Fußball. KI - Künstliche Intelligenz, 27(3), 235–240.
Schoenfeld, F., & Wiskott, L. (2013). RatLab: An easy to use tool for place code simulations. Frontiers in Computational Neuroscience, 7(104). http://doi.org/10.3389/fncom.2013.00104
Tossi, G., Stude, P., Schwenkreis, P., Tegenthoff, M., & Dinse, H. R. (2013). Behavioural and neurophysiological markers reveal differential sensitivity to homeostatic interactions between centrally and peripherally applied passive stimulation. European Journal of Neuroscience, 38(6), 2893–2901.
Tschentscher, M., Neuhausen, M., Koch, C., König, M., Salmen, J., & Schlipsing, M. (2013). Comparing Image Features and Machine Learning Algorithms for Real-time Parking-space Classifiaction. In Proceedings of the ASCE International Workshop on Computing in Civil Engineering (pp. 363–370).
Wang, N., Jancke, D., & Wiskott, L. (2013). Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines. arXiv preprint arXiv:1312.6108.
2012

Beste, C., Wascher, E., Dinse, H. R., & Saft, C. (2012). Faster perceptual learning through excitotoxic neurodegeneration. Curr. Biol., 22(20), 1914–1917.
Grimme, B., Lipinski, J., & Schöner, G. (2012). Naturalistic arm movements during obstacle avoidance in 3D and the identification of movement primitives. Experimental brain research, 222(3), 185–200. http://doi.org/10.1007/s00221-012-3205-6
Schlieper, S., & Dinse, H. R. (2012). Perceptual improvement following repetitive sensory stimulation depends monotonically on stimulation intensity. Brain Stimul, 5(4), 647–651.
Walther, T., & Würtz, R. P. (2012). Unsupervised Learning of Face Detection Models from Unlabeled Image Streams. In A. Brömme & Busch, C. (Eds.), Proceedings of the 11th International Conference of the Biometrics Special Interest Group (Vol. P-196, pp. 221–231). Bonn: Köllen.
Hoffken, O., Lenz, M., Hockelmann, N., Dinse, H. R., & Tegenthoff, M. (2012). Noradrenergic modulation of human visual cortex excitability assessed by paired-pulse visual-evoked potentials. Neuroreport, 23(12), 707–711.
Dinse, H. R. (2012). Choosing to improve or to impair. Clin Neurophysiol, 123(6), 1063–1064.
Lenz, M., Tegenthoff, M., Kohlhaas, K., Stude, P., Hoffken, O., Gatica Tossi, M. A., et al. (2012). Increased excitability of somatosensory cortex in aged humans is associated with impaired tactile acuity. J. Neurosci., 32(5), 1811–1816.
Wilimzig, C., Ragert, P., & Dinse, H. R. (2012). Cortical topography of intracortical inhibition influences the speed of decision making. Proc. Natl. Acad. Sci. U.S.A., 109(8), 3107–3112.
Canu, M. H., Coq, J. O., Barbe, M. F., & Dinse, H. R. (2012). Plasticity of adult sensorimotor system. Neural Plast., 2012, 768259.
Doğan, Ü., Glasmachers, T., & Igel, C. (2012). Turning Binary Large-margin Bounds into Multi-class Bounds. In ICML workshop on RKHS and kernel-based methods.
Doğan, Ü., Glasmachers, T., & Igel, C. (2012). A Note on Extending Generalization Bounds for Binary Large-margin Classifiers to Multiple Classes. In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD).
Duran,, & Sandamirskaya, Y. (2012). Neural Dynamics of Hierarchically Organized Sequences: a Robotic Implementation. In Proceedings of 2012 IEEE-RAS International Conference on Humanoid Robots (Humanoids).
Duran, B., Sandamirskaya, Y., & Schöner, G. (2012). A Dynamic Field Architecture for the Generation of Hierarchically Organized Sequences. In A. E. P. Villa, Duch, W., Érdi, P., Masulli, F., & Palm, G. (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2012 (Vol. 7552, pp. 25–32). Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-33269-2_4
Escalante-B., A. N., & Wiskott, L. (2012). Slow Feature Analysis: Perspectives for Technical Applications of a Versatile Learning Algorithm. Künstliche Intelligenz [Artificial Intelligence], 26(4), 341–348. Retrieved from http://www.springerlink.com/content/vk3738325250162k/
Freyer, F., Reinacher, M., Nolte, G., Dinse, H. R., & Ritter, P. (2012). Repetitive tactile stimulation changes resting-state functional connectivity-implications for treatment of sensorimotor decline. Front Hum Neurosci, 6, 144.
Glasmachers, T. (2012). Convergence of the IGO-Flow of Isotropic Gaussian Distributions on Convex Quadratic Problems. In C. C. Coello, Cutello, V., Deb, K., Forrest, S., Nicosia, G., & Pavone, M. (Eds.), Parallel Problem Solving from Nature (PPSN). Springer.
Glasmachers, T., Koutník, J., & Schmidhuber, J. (2012). Kernel Representations for Evolving Continuous Functions. Journal of Evolutionary Intelligence, 5(3), 171–187. http://doi.org/10.1007/s12065-012-0070-y
Grabska-Barwińska, A., Ng, B. S. W., & Jancke, D. (2012). Orientation selective or not?–Measuring significance of tuning to a circular parameter. Journal of neuroscience methods, 203(1), 1–9.
Kalisch, T., Kattenstroth, J. C., Kowalewski, R., Tegenthoff, M., & Dinse, H. R. (2012). Age-related changes in the joint position sense of the human hand. Clin Interv Aging, 7, 499–507.
Kalisch, T., Kattenstroth, J. C., Kowalewski, R., Tegenthoff, M., & Dinse, H. R. (2012). Cognitive and tactile factors affecting human haptic performance in later life. PLoS ONE, 7(1), e30420.
Kattenstroth, J. C., Kalisch, T., Peters, S., Tegenthoff, M., & Dinse, H. R. (2012). Long-term sensory stimulation therapy improves hand function and restores cortical responsiveness in patients with chronic cerebral lesions. Three single case studies. Front Hum Neurosci, 6, 244.
Klaes, C., Schneegans, S., Schöner, G., & Gail, A. (2012). Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making. PLoS computational biology, 8(11), e1002774.
Kompella, V. R., Luciw, M., & Schmidhuber, J. (2012). Incremental slow feature analysis: Adaptive low-complexity slow feature updating from high-dimensional input streams. Neural Computation, 24(11), 2994–3024.
Kompella, V. R., Luciw, M., Stollenga, M., Pape, L., & Schmidhuber, J. (2012). Autonomous learning of abstractions using curiosity-driven modular incremental slow feature analysis. In Development and Learning and Epigenetic Robotics (ICDL), 2012 IEEE International Conference on (pp. 1–8). IEEE.
Kompella, V. R., & Sturm, P. (2012). Collective-reward based approach for detection of semi-transparent objects in single images. Computer Vision and Image Understanding, 116(4), 484–499.
Kowalewski, R., Kattenstroth, J. C., Kalisch, T., & Dinse, H. R. (2012). Improved acuity and dexterity but unchanged touch and pain thresholds following repetitive sensory stimulation of the fingers. Neural Plast., 2012, 974504.
Lins, J., Schneegans, S., Spencer, J., & Schöner, G. (2012). The Function and Fallibility of Visual Feature Integration: A Dynamic Neural Field Model of Illusory Conjunctions. Frontiers in Computational Neuroscience, (128). http://doi.org/10.3389/conf.fncom.2012.55.00128
Lipinski, J., Schneegans, S., Sandamirskaya, Y., Spencer, J. P., & Schöner, G. (2012). A Neuro-Behavioral Model of Flexible Spatial Language Behaviors. Journal of Experimental Psychology: Learning, Memory and Cognition., 38(6), 1490–1511.
Luciw, M., Kompella, V. R., & Schmidhuber, J. (2012). Hierarchical incremental slow feature analysis. Workshop on Deep Hierarchies in Vision.
Müller, M. K., Tremer, M., Bodenstein, C., & Würtz, R. P. (2012). Lernen situationsunabhängiger Personenerkennung. Informatikspektrum, 35(2), 112–118. http://doi.org/10.1007/s00287-012-0598-3
Park, E., Schöner, G., & Scholz, J. P. (2012). Functional synergies underlying control of upright posture during changes in head orientation. PLoS ONE, 7(8), 1–12. http://doi.org/10.1371/journal.pone.0041583
Richter, M., Sandamirskaya, Y., & Schöner, G. (2012). A robotic architecture for action selection and behavioral organization inspired by human cognition. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS.
Salmen, J., Houben, S., & Schlipsing, M. (2012). Google Street View Images Support the Development of Vision-Based Driver Assistance Systems. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 891–895).
Schlipsing, M., Salmen, J., Lattke, B., Schröter, K., & Winner, H. (2012). Roll Angle Estimation for Motorcycles: Comparing Video and Inertial Sensor Approaches. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 500–505).
Schneegans, S., & Schöner, G. (2012). A neural mechanism for coordinate transformation predicts pre-saccadic remapping. Biological cybernetics, 106(2), 89–109.
Scholz, J. P., Park, E., Jeka, J. J., Schöner, G., & Kiemel, T. (2012). How visual information links to multijoint coordination during quiet standing. Experimental Brain Research, 222, 229–239. http://doi.org/10.1007/s00221-012-3210-9
Schönfeld, F., & Wiskott, L. (2012). Sensory integration of place and head-direction cells in a virtual environment. Poster at NeuroVisionen 8, 26. Oct 2012, Aachen, Germany.
Schönfeld, F., & Wiskott, L. (2012). Sensory integration of place and head-direction cells in a virtual environment. Poster at the 8th FENS Forum of Neuroscience, Jul 14–18, Barcelona, Spain.
Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2012). Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition. Neural Networks, 32, 323–332.
Tschentscher, M. (2012). Evaluation von Monocular Inverse Depth SLAM zur Stützung von Fahrzeugodometrie (Masterarbeit).
Tschentscher, M., & Neuhausen, M. (2012). Video-based Parking-space Detection. In Proceedings of the Forum Bauinformatik (pp. 159–166).
Tuma, M., Igel, C., & Prior, M. (2012). Hydroacoustic Signal Classification Using Support Vector Machines. In C. Chen (Ed.), Signal and Image Processing for Remote Sensing, 2nd ed. (pp. 37–56). CRC Press.
van Hengel, U., Sandamirskaya, Y., Schneegans, S., & Schöner, G. (2012). A neural-dynamic architecture for flexible spatial language: intrinsic frames, the term “between”, and autonomy. In 21st IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man) 2012 (pp. 150–157).
Wang, N., Melchior, J., & Wiskott, L. (2012). An Analysis of Gaussian-Binary Restricted Boltzmann Machines for Natural Images. In Proc. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 25–27, Bruges, Belgium (pp. 287–292).
2011

Heinisch, C., Dinse, H. R., Tegenthoff, M., Juckel, G., & Brune, M. (2011). An rTMS study into self-face recognition using video-morphing technique. Soc Cogn Affect Neurosci, 6(4), 442–449.
Beste, C., Wascher, E., Gunturkun, O., & Dinse, H. R. (2011). Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning. Curr. Biol., 21(10), 876–882.
Hock, H. S., Schöner, G., Brownlow, S., & Taler, D. (2011). The temporal dynamics of global-to-local feedback in the formation of hierarchical motion patterns: psychophysics and computational simulations. Attention, perception & psychophysics, 73(4), 1171–94. http://doi.org/10.3758/s13414-011-0105-y
Böhringer, S., van der Lijn, F., Liu, F., Sinigerova, S., Birnbaum, S., Mangold, E., et al. (2011). Genetic determination of the human facial shape: links between cleft-lips and normal variation. European Journal of Human Genetics, 19, 1192–1197. http://doi.org/10.1038/ejhg.2011.110
Chavane, F., Sharon, D., Jancke, D., Marre, O., Frégnac, Y., & Grinvald, A. (2011). Lateral spread of orientation selectivity in V1 is controlled by intracortical cooperativity. Frontiers in Systems Neuroscience, 5.
Cuccu, G., Gomez, F., & Glasmachers, T. (2011). Novelty Restarts for Evolution Strategies. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC). IEEE.
Cuccu, G., Gomez, F., & Glasmachers, T. (2011). Novelty Restarts for Evolution Strategies. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC). IEEE.
Dinse, H. R. (2011). Brain Plasticity and Touch . In M. J. Hertenstein & Weiss, S. J. (Eds.), The Handbook of Touch: neuroscience, behavioral, and health perspectives (pp. 85–120). New York : Springer .
Dinse, H. R., Kattenstroth, J. C., Gatica Tossi, M. A., Tegenthoff, M., & Kalisch, T. (2011). Sensory stimulation for augmenting perception, sensorimotor behaviour and cognition . In H. Markram & Segev, I. (Eds.), Augmenting Cognition (pp. 11–39). Lausanne : EPFL Press .
Dinse, H. R., Kattenstroth, J. C., Tegenthoff, M., & Kalisch, T. (2011). Plastizität, motorisches Lernen und sensible Stimulation . In C. Dettmers & Stephan, K. M. (Eds.), Motorische Therapie nach Schlaganfall (pp. 17–43). : Hippocampus .
Doğan, Ü., Glasmachers, T., & Igel, C. (2011). Fast Training of Multi-Class Support Vector Machines (No. 2011/3). Department of Computer Science, University of Copenhagen.
Escalante, A., & Wiskott, L. (2011). Heuristic Evaluation of Expansions for Non-Linear Hierarchical Slow Feature Analysis. In Proc. The 10th Intl. Conf. on Machine Learning and Applications (ICMLA′11), Dec 18–21, Honolulu, Hawaii (pp. 133–138). IEEE Computer Society. http://doi.org/10.1109/ICMLA.2011.72
Geissler, M., Dinse, H. R., Neuhoff, S., Kreikemeier, K., & Meier, C. (2011). Human umbilical cord blood cells restore brain damage induced changes in rat somatosensory cortex. PLoS ONE, 6(6), e20194.
Glasmachers, T., & Schmidhuber, J. (2011). Optimal Direct Policy Search. In Proceedings of the 4th Conference on Artificial General Intelligence (AGI).
Gopinath, K., Ringe, W., Goyal, A., Carter, K., Dinse, H. R., Haley, R., & Briggs, R. (2011). Striatal functional connectivity networks are modulated by fMRI resting state conditions. Neuroimage, 54(1), 380–388.
Graziano, V., Glasmachers, T., Schaul, T., Pape, L., Cuccu, G., Leitner, J., & Schmidhuber, J. (2011). Artificial Curiosity for Autonomous Space Exploration. ACTA FUTURA.
Grimme, B., Fuchs, S., Perrier, P., & Schöner, G. (2011). Limb versus speech motor control: a conceptual review. Motor control, 15(1), 5–33. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21339512
Houben, S. (2011). A single target voting scheme for traffic sign detection. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 124–129).
Kalisch, T., Kattenstroth, J. C., Noth, S., Tegenthoff, M., & Dinse, H. R. (2011). Rapid assessment of age-related differences in standing balance. J Aging Res, 2011, 160490.
Kalisch, T., Richter, J., Lenz, M., Kattenstroth, J. C., Kolankowska, I., Tegenthoff, M., & Dinse, H. R. (2011). Questionnaire-based evaluation of everyday competence in older adults. Clin Interv Aging, 6, 37–46.
Kattenstroth, J. C., Kalisch, T., Kolankowska, I., & Dinse, H. R. (2011). Balance, sensorimotor, and cognitive performance in long-year expert senior ballroom dancers. J Aging Res, 2011, 176709.
Kompella, V. R., Luciw, M. D., & Schmidhuber, J. (2011). Incremental Slow Feature Analysis. IJCAI, 11, 1354–1359.
Kompella, V. R., Pape, L., Masci, J., Frank, M., & Schmidhuber, J. (2011). Autoincsfa and vision-based developmental learning for humanoid robots. In Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on (pp. 622–629). IEEE.
Kompella, V. R., & Sturm, P. (2011). Detection and avoidance of semi-transparent obstacles using a collective-reward based approach. In Robotics and Automation (ICRA), 2011 IEEE International Conference on (pp. 3469–3474). IEEE.
Onat, S., König, P., & Jancke, D. (2011). Natural scene evoked population dynamics across cat primary visual cortex captured with voltage-sensitive dye imaging. Cerebral cortex, 21(11), 2542–2554.
Onat, S., Nortmann, N., Rekauzke, S., König, P., & Jancke, D. (2011). Independent encoding of grating motion across stationary feature maps in primary visual cortex visualized with voltage-sensitive dye imaging. Neuroimage, 55(4), 1763–1770.
Reimann, H., Iossifidis, I., & Schöner, G. (2011). Autonomous movement generation for manipulators with multiple simultaneous constraints using the attractor dynamics approach. In 2011 IEEE International Conference on Robotics and Automation, ICRA2011.
Rothermel, M., Ng, B. S. W., Grabska-Barwińska, A., Hatt, H., & Jancke, D. (2011). Nasal chemosensory-stimulation evoked activity patterns in the rat trigeminal ganglion visualized by in vivo voltage-sensitive dye imaging. PloS one, 6(10), e26158.
Salmen, J., Caup, L., & Igel, C. (2011). Real-time estimation of optical flow based on optimized Haar wavelet features. In Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization (pp. 448–461).
Sandamirskaya, Y., Richter, M., & Schöner, G. (2011). A neural-dynamic architecture for behavioral organization of an embodied agent. In IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2011) (pp. 1–7).
Schaul, T., Glasmachers, T., & Schmidhuber, J. (2011). High Dimensions and Heavy Tails for Natural Evolution Strategies. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Schaul, T., Pape, L., Glasmachers, T., Graziano, V., & Schmidhuber, J. (2011). Coherence Progress: A Measure of Interestingness Based on Fixed Compressors. In Proceedings of the 4th Conference on Artificial General Intelligence (AGI).
Schlipsing, M., Schepanek, J., & Salmen, J. (2011). Video-Based Roll Angle Estimation for Two-Wheeled Vehicles. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 876–881).
Schneider, H. J., Kosilek, R. P., Günther, M., Schopohl, J., Römmler, J., Stalla, G. K., et al. (2011). A novel approach for the detection of acromegaly: accuracy of diagnosis by automatic face classification. Journal of Clinical Endocrinology and Metabolism, 96(7), 2074–2080. http://doi.org/10.1210/jc.2011-0237
Scholz, J. P., Dwight-Higgin, T., Lynch, J. E., Tseng, Y. -W., Martin, V., & Schöner, G. (2011). Motor equivalence and self-motion induced by different movement speeds. Experimental Brain Research, 209(3), 319–332. http://doi.org/10.1007/s00221-011-2541-2
Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2011). The German Traffic Sign Recognition Benchmark: A multi-class classification competition. In Proceedings of the IEEE International Joint Conference on Neural Networks (pp. 1453–1460).
Tuma, M., & Igel, C. (2011). Improved working set selection for LaRank. In A. Berciano, Díaz-Pernil, D., Kropatsch, W., Molina-Abril, H., & Real, P. (Eds.), Proceedings of the 14th International Conference on Computer Analysis of Images and Patterns (CAIP) (Vol. 6854, pp. 327–334). Springer Press.
Walther, T., & Würtz, R. P. (2011). Learning to Look at Humans. In C. Müller-Schloer, Schmeck, H., & Ungerer, T. (Eds.), Organic Computing - a Paradigm Shift for Complex Systems (pp. 309–322). Springer. http://doi.org/10.1007/978-3-0348-0130-0_20
Zibner, S. K. U., Faubel, C., Iossifidis, I., & Schöner, G. (2011). Dynamic Neural Fields as Building Blocks of a Cortex-Inspired Architecture for Robotic Scene Representation. IEEE Transactions on Autonomous Mental Development, 3(1), 74–91.
Zibner, S. K. U., Faubel, C., & Schöner, G. (2011). Making a robotic scene representation accessible to feature and label queries. In Proceedings of the First Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL EPIROB 2011).
2010

Meyer, Q., Schönfeld, F., Stamminger, M., & Wanka, R. (2010). 3-SAT on CUDA: Towards a massively parallel SAT solver. In 2010 International Conference on High Performance Computing Simulation (pp. 306–313). http://doi.org/10.1109/HPCS.2010.5547116
David-Jurgens, M., & Dinse, H. R. (2010). Effects of aging on paired-pulse behavior of rat somatosensory cortical neurons. Cereb. Cortex, 20(5), 1208–1216.
Donatti, G. S., Lomp, O., & Würtz, R. P. (2010). Evolutionary Optimization of Growing Neural Gas Parameters for Object Categorization and Recognition. In Proc. IJCNN (pp. 1862–1869). IEEE Computer Society, Los Alamitos, CA.
Escalante, A., & Wiskott, L. (2010). Gender and Age Estimation from Synthetic Face Images with Hierarchical Slow Feature Analysis. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU′10), Jun 28 – Jul 2, Dortmund. Retrieved from http://www.springerlink.com/content/r031104qv7228r35
Faubel, C., & Zibner, S. K. U. (2010). A neuro-dynamic object recognition architecture enhanced by foveal vision and a gaze control mechanism. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on (pp. 1171–1176). IEEE.
Gera, G., Freitas, S., Latash, M., Monahan, K., Schöner, G., & Scholz, J. (2010). Motor Abundance Contributes to Resolving Multiple Kinematic Task Constraints. Motor Control, 14, 83–115.
Glasmachers, T. (2010). Universal Consistency of Multi-Class Support Vector Classification. In Advances in Neural Information Processing Systems (NIPS).
Glasmachers, T., & Igel, C. (2010). Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(8), 1522–1528.
Glasmachers, T., Schaul, T., & Schmidhuber, J. (2010). A Natural Evolution Strategy for Multi-Objective Optimization. In Parallel Problem Solving from Nature (PPSN). Springer.
Glasmachers, T., Schaul, T., Sun, Y., Wierstra, D., & Schmidhuber, J. (2010). Exponential Natural Evolution Strategies. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).
Günther, M., Müller, M. K., & Würtz, R. P. (2010). Two kinds of statistics for better face recognition. In T. E. Simos, Psihoyios, G., & Tsitouras, C. (Eds.), Numerical Analysis and Applied Mathematics, International Conference (pp. 1901–1904). American Institute of Physics.
Hock, H. S., & Schöner, G. (2010). Measuring Perceptual Hysteresis with the Modified Method of Limits: Dynamics at the Threshold. Seeing and Perceiving, 23, 173–195.
Jancke, D., Chavane, F., & Grinvald, A. (2010). Stimulus Localization by Neuronal Populations in Early Visual Cortex: Linking Functional Architecture to Perception. In Dynamics of Visual Motion Processing (pp. 95–116). Springer.
Jancke, D., & Erlhagen, W. (2010). Bridging the Gap: A Model of Common Neural Mechanisms Underlying the Fröhlich Effect, the Flash-Lag Effect, and the Representational Momentum Effect. In Space and Time in Perception and Action (pp. 422–440). Cambridge: Cambridge University Press. http://doi.org/10.1017/CBO9780511750540.025
Kalisch, T., Tegenthoff, M., & Dinse, H. R. (2010). Repetitive electric stimulation elicits enduring improvement of sensorimotor performance in seniors. Neural Plast., 2010, 690531.
Kattenstroth, J. C., Kolankowska, I., Kalisch, T., & Dinse, H. R. (2010). Superior sensory, motor, and cognitive performance in elderly individuals with multi-year dancing activities. Front Aging Neurosci, 2, .
Latash, M., Levin, M. F., Scholz, J. P., & Schöner, G. (2010). Motor control theories and their applications. Medicina (Kaunas), 29(6), 997–1003. http://doi.org/10.1016/j.biotechadv.2011.08.021.Secreted
Markounikau, V., Igel, C., Grinvald, A., & Jancke, D. (2010). A dynamic neural field model of mesoscopic cortical activity captured with voltage-sensitive dye imaging. PLoS computational biology, 6(9), e1000919.
Ng, B. S. W., Grabska-Barwińska, A., Güntürkün, O., & Jancke, D. (2010). Dominant vertical orientation processing without clustered maps: early visual brain dynamics imaged with voltage-sensitive dye in the pigeon visual Wulst. J Neurosci, 30(19), 6713–6725.
Salmen, J., Schlipsing, M., & Igel, C. (2010). Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis. Pattern Recognition Letters, 31, 1903–1907.
Sandamirskaya, Y., Lipinski, J., Iossifidis, I., & Schöner, G. (2010). Natural human-robot interaction through spatial language: a dynamic neural fields approach. In 19th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN (pp. 600–607). Viareggio, Italy. http://doi.org/10.1109/ROMAN.2010.5598671
Sandamirskaya, Y., & Schöner, G. (2010). An embodied account of serial order: how instabilities drive sequence generation. Neural Networks, 23(10), 1164–1179. http://doi.org/DOI: 10.1016/j.neunet.2010.07.012
Sandamirskaya, Y., & Schöner, G. (2010). Serial order in an acting system: a multidimensional dynamic neural fields implementation. In Development and Learning, 2010. ICDL 2010. 9th IEEE International Conference on.
Sun, Y., Glasmachers, T., Schaul, T., & Schmidhuber, J. (2010). Frontier Search. In Proceedings of the 3rd Conference on Artificial General Intelligence (AGI).
Tschentscher, M. (2010). Effiziente Berechnung von 3D-Flußvektoren (Scene Flow) (Bachelorarbeit).
Tuma, M., Igel, C., & Prior, M. (2010). Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets. In Proc. of the 20th International Conference on Pattern Recognition (ICPR) (pp. 1011–1014).
Walther, T., & Würtz, R. P. (2010). Learning Generic Human Body Models. In F. J. Perales & Fisher, R. B. (Eds.), Proc. Sixth Conference on Articulated Motion and Deformable Objects (pp. 98–107). Springer.
Würtz, R. P., Bellman, K. L., Schmeck, H., & Igel, C. (2010). Editorial: Special Issue on Organic Computing. ACM Transactions on Autonomous and Adaptive Systems, 5(3), 1–3. http://doi.org/10.1145/1837909.1837910
Zibner, S. K. U., Faubel, C., Iossifidis, I., & Schöner, G. (2010). Scene Representation for Anthropomorphic Robots: A Dynamic Neural Field Approach. In ISR / ROBOTIK 2010. Munich, Germany.
Zibner, S. K. U., Faubel, C., Iossifidis, I., Schöner, G., & Spencer, J. P. (2010). Scenes and tracking with dynamic neural fields: How to update a robotic scene representation. In Development and Learning (ICDL), 2010 IEEE 9th International Conference on (pp. 244–250). IEEE.
2009

Leonhardt, R., & Dinse, H. R. (2009). Receptive field plasticity of area 17 visual cortical neurons of adult rats. Exp Brain Res, 199(3-4), 401–410.
Smith, P. S., Dinse, H. R., Kalisch, T., Johnson, M., & Walker-Batson, D. (2009). Effects of repetitive electrical stimulation to treat sensory loss in persons poststroke. Arch Phys Med Rehabil, 90(12), 2108–2111.
Johnson, J. S., Spencer, J. P., & Schöner, G. (2009). A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory. Brain research, 1299, 17–32. http://doi.org/10.1016/j.brainres.2009.07.008
Johnson, J. S., Spencer, J. P., & Schöner, G. (2009). A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory. Brain research, 1299, 17–32. http://doi.org/10.1016/j.brainres.2009.07.008
Hock, H. S., Schöner, G., & Gilroy, L. (2009). A counterchange mechanism for the perception of motion. Acta psychologica, 132(1), 1–21. http://doi.org/10.1016/j.actpsy.2009.06.006
Hoffken, O., Stude, P., Lenz, M., Bach, M., Dinse, H. R., & Tegenthoff, M. (2009). Visual paired-pulse stimulation reveals enhanced visual cortex excitability in migraineurs. Eur. J. Neurosci., 30(4), 714–720.
Kalisch, T., Ragert, P., Schwenkreis, P., Dinse, H. R., & Tegenthoff, M. (2009). Impaired tactile acuity in old age is accompanied by enlarged hand representations in somatosensory cortex. Cereb. Cortex, 19(7), 1530–1538.
Lissek, S., Wilimzig, C., Stude, P., Pleger, B., Kalisch, T., Maier, C., et al. (2009). Immobilization impairs tactile perception and shrinks somatosensory cortical maps. Curr. Biol., 19(10), 837–842.
Dinse, H. R. (2009). Gehirne begreifen und erfassen: Tasten – der unterschätzte Sinn . In R. Rosenzweig (Ed.), Nicht wahr?! - Sinneskanäle, Hirnwindungen und Grenzen der Wahrnehmung (pp. 133–164). : mentis Verlag .
Dinse, H. R., Tegenthoff, M., Heinisch, C., & Kalisch, T. (2009). Ageing and Touch . In B. Goldstein (Ed.), The Sage Encyclopedia of Perception (pp. 21–24). : Sage .
Donatti, G. S., & Würtz, R. P. (2009). Using Growing Neural Gas Networks to represent visual object knowledge. In Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence (pp. 54–58). IEEE Computer Society, Newark, NJ.
Grabska-Barwińska, A., Distler, C., Hoffmann, K. -P., & Jancke, D. (2009). Contrast independence of cardinal preference: stable oblique effect in orientation maps of ferret visual cortex. European Journal of Neuroscience, 29(6), 1258–1270.
Günther, M., & Würtz, R. P. (2009). Face Detection and Recognition Using Maximum Likelihood Classifiers on Gabor Graphs. International Journal of Pattern Recognition and Artificial Intelligence, 23(3), 433–461. http://doi.org/10.1142/S0218001409007211
Langner, G., Dinse, H. R., & Godde, B. (2009). A map of periodicity orthogonal to frequency representation in the cat auditory cortex. Front Integr Neurosci, 3, 27.
Lipinski, J., Sandamirskaya, Y., & Schöner, G. (2009). Swing it to the Left, Swing it to the Right: Enacting Flexible Spatial Language Using a Neurodynamic Framework. Cognitive Neurodynamics, 3(4).
Lipinski, J., Sandamirskaya, Y., & Schöner, G. (2009). An Integrative Framework for Spatial Language and Color: Robotic Demonstrations Using the Dynamic Field Theory. In 31th Annual Meeting of the Cognitive Science Society, CogSci 2009. Amstredam, NL.
Lipinski, J., Sandamirskaya, Y., & Schöner, G. (2009). Behaviorally Flexible Spatial Communication: Robotic Demonstrations of a Neurodynamic Framework. In B. Mertsching, Hund, M., & Z., A. (Eds.), KI 2009, Lecture Notes in Artificial Intelligence (Vol. 5803, pp. 257–264). Berlin: Springer-Verlag.
Markounikau, V., Igel, C., & Jancke, D. (2009). A Mesoscopic Model of VSD Dynamics Observed in Visual Cortex Induced by Flashed and Moving Stimuli. In Frontiers in Computational Neuroscience (p. 64). Frontiers.
Martin, V., Scholz, J. P., & Schöner, G. (2009). Redundancy, self-motion and motor control. Neural Computation, 21(5), 1371–1414.
Müller, M. K., & Würtz, R. P. (2009). Learning from Examples to Generalize over Pose and Illumination. In C. Alippi, Polycarpou, M., Panayiotou, C., & Ellinas, G. (Eds.), Artificial Neural Networks - ICANN 2009 (Vol. 5769, pp. 643–652). Springer.
Palagina, G., Eysel, U. T., & Jancke, D. (2009). Strengthening of lateral activation in adult rat visual cortex after retinal lesions captured with voltage-sensitive dye imaging in vivo. Proceedings of the National Academy of Sciences, 106(21), 8743–8747.
Rothermel, M., Ng, B., Hatt, H., & Jancke, D. (2009). Voltage-Sensitive Dye Imaging of Odor Evoked Activity Patterns in the Trigeminal Ganglion in vivo. In CHEMICAL SENSES (Vol. 34, pp. A30–A31). OXFORD UNIV PRESS GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND.
Salmen, J., Schlipsing, M., Edelbrunner, J., Hegemann, S., & Lueke, S. (2009). Real-Time Stereo Vision: Making more out of Dynamic Programming. In Proceedings of the International Conference on Computer Analysis of Images and Patterns (pp. 1096–1103).
Tuma, M., Iossifidis, I., & Schöner, G. (2009). Temporal stabilization of discrete movement in variable environments: an attractor dynamics approach. In IEEE International Conference on Robotics and Automation (ICRA) (pp. 863–868).
Walther, T., & Würtz, R. P. (2009). Unsupervised learning of human body parts from video footage. In Proceedings of ICCV workshops, Kyoto (pp. 336–343). IEEE Computer Society, Los Alamitos, CA.
Westphal, G., & Würtz, R. P. (2009). Combining Feature- and Correspondence-Based Methods for Visual Object Recognition. Neural Computation, 21(7), 1952–1989. http://doi.org/10.1162/neco.2009.12-07-675
Westphal, G., & Würtz, R. P. (2009). Combining Feature- and Correspondence-Based Methods for Visual Object Recognition. Neural Computation, 21(7), 1952–1989. http://doi.org/10.1162/neco.2009
2008

Benali, A., Weiler, E., Benali, Y., Dinse, H. R., & Eysel, U. T. (2008). Excitation and inhibition jointly regulate cortical reorganization in adult rats. J. Neurosci., 28(47), 12284–12293.
Bliem, B., Muller-Dahlhaus, J. F., Dinse, H. R., & Ziemann, U. (2008). Homeostatic metaplasticity in the human somatosensory cortex. J Cogn Neurosci, 20(8), 1517–1528.
Hoffken, O., Grehl, T., Dinse, H. R., Tegenthoff, M., & Bach, M. (2008). Paired-pulse behavior of visually evoked potentials recorded in human visual cortex using patterned paired-pulse stimulation. Exp Brain Res, 188(3), 427–435.
David-Jurgens, M., Churs, L., Berkefeld, T., Zepka, R. F., & Dinse, H. R. (2008). Differential effects of aging on fore- and hindpaw maps of rat somatosensory cortex. PLoS ONE, 3(10), e3399.
Dinse, H. R. (2008). Haptic Banknote Design . In M. Grunwald (Ed.), Human Haptic Perception - Basics and Applications (pp. 537–547). : Birkhäuser .
Dinse, H. R., Wilimzig, C., & Kalisch, T. (2008). Learning in Haptic Perception . In M. Grunwald (Ed.), Human Haptic Perception - Basics and Applications (pp. 165–182). : Birkhäuser .
Glasmachers, T. (2008). On related violating pairs for working set selection in SMO algorithms. In M. Verleysen (Ed.), Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN). d-side publications.
Glasmachers, T. (2008). Gradient Based Optimization of Support Vector Machines. Doctoral thesis, Fakultät für Mathematik, Ruhr-Universität Bochum, Germany.
Glasmachers, T., & Igel, C. (2008). Second-Order SMO Improves SVM Online and Active Learning. Neural Computation, 20(2), 374–382.
Glasmachers, T., & Igel, C. (2008). Uncertainty Handling in Model Selection for Support Vector Machines. In G. Rudolph, Jansen, T., Lucas, S., Poloni, C., & Beume, N. (Eds.), Parallel Problem Solving from Nature (PPSN) (pp. 185–194). Springer.
Igel, C., Heidrich-Meisner, V., & Glasmachers, T. (2008). Shark. Journal of Machine Learning Research, 9, 993–996.
Kalisch, T., Tegenthoff, M., & Dinse, H. R. (2008). Improvement of sensorimotor functions in old age by passive sensory stimulation. Clin Interv Aging, 3(4), 673–690.
Krüger, M., von der Malsburg, C., & Würtz, R. P. (2008). Self-organized evaluation of dynamic hand gestures for sign language recognition. In R. P. Würtz (Ed.), Organic Computing (pp. 321–342). Springer.
Lessmann, M., & Würtz, R. P. (2008). Image Segmentation by a Network of Cortical Macrocolumns with Learned Connection Weights. In M. Hinchey, Pagnonia, A., Rammig, F. J., & Schmeck, H. (Eds.), Proceedings of Biologically-Inspired Collaborative Computing (BICC), Milano, Sep. 2008 (pp. 177–186). Springer.
Ragert, P., Franzkowiak, S., Schwenkreis, P., Tegenthoff, M., & Dinse, H. R. (2008). Improvement of tactile perception and enhancement of cortical excitability through intermittent theta burst rTMS over human primary somatosensory cortex. Exp Brain Res, 184(1), 1–11.
Ragert, P., Kalisch, T., Bliem, B., Franzkowiak, S., & Dinse, H. R. (2008). Differential effects of tactile high- and low-frequency stimulation on tactile discrimination in human subjects. BMC Neurosci, 9, 9.
Schneegans, S., & Schöner, G. (2008). Dynamic Field Theory as a framework for understanding embodied cognition. In P. Calvo & Gomila, T. (Eds.), Handbook of cognitive science: An embodied approach (pp. 241–271). Amsterdam, Netherlands: Elsevier.
Vollmar, T., Maus, B., Würtz, R. P., Gillessen-Kaesbach, G., Horsthemke, B., Wieczorek, D., & Böhringer, S. (2008). Impact of geometry and viewing angle on classification accuracy of 2D based analysis of dysmorphic faces. European Journal of Medical Genetics, 51, 44–53. http://doi.org/10.1016/j.ejmg.2007.10.002
Westphal, G., von der Malsburg, C., & Würtz, R. P. (2008). Feature-driven emergence of model graphs for object recognition and categorization. In A. Kandel, Bunke, H., & Last, M. (Eds.), Applied Pattern Recognition (pp. 155–199). Springer.
Würtz, R. P. (2008). Organic Computing for Image Understanding and Robotics.
Würtz_(editor),. (2008). Organic Computing. Springer. http://doi.org/10.1007/978-3-540-77657-4
2007

Schwenkreis, P., El Tom, S., Ragert, P., Pleger, B., Tegenthoff, M., & Dinse, H. R. (2007). Assessment of sensorimotor cortical representation asymmetries and motor skills in violin players. Eur. J. Neurosci., 26(11), 3291–3302.
Hoffken, O., Veit, M., Knossalla, F., Lissek, S., Bliem, B., Ragert, P., et al. (2007). Sustained increase of somatosensory cortex excitability by tactile coactivation studied by paired median nerve stimulation in humans correlates with perceptual gain. J. Physiol. (Lond.), 584(Pt 2), 463–471.
Bliem, B., Frombach, E., Ragert, P., Knossalla, F., Woitalla, D., Tegenthoff, M., & Dinse, H. R. (2007). Dopaminergic influences on changes in human tactile acuity induced by tactile coactivation. Exp Brain Res, 181(1), 131–137.
McNamara, A., Tegenthoff, M., Dinse, H., Buchel, C., Binkofski, F., & Ragert, P. (2007). Increased functional connectivity is crucial for learning novel muscle synergies. Neuroimage, 35(3), 1211–1218.
Seitz, A. R., & Dinse, H. R. (2007). A common framework for perceptual learning. Curr. Opin. Neurobiol., 17(2), 148–153.
Dinse, H. R., Ragert, P., & Tegenthoff, M. (2007). Somatosensorik . In H. Siebner & Ziemann, U. (Eds.), Das TMS-Buch. Transkranielle Magnetstimulation (pp. 439–448). Heidelberg : Springer .
Igel, C., Glasmachers, T., Mersch, B., Pfeifer, N., & Meinicke, P. (2007). Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 4(2), 216–226.
Kalisch, T., Tegenthoff, M., & Dinse, H. R. (2007). Differential effects of synchronous and asynchronous multifinger coactivation on human tactile performance. BMC Neurosci, 8, 58.
Kusnezow, W., Horn, W., & Würtz, R. P. (2007). Fast image processing with constraints by solving linear PDEs. Electronic Letters on Computer Vision and Image Analysis, 6(2), 22–35.
Mersch, B., Glasmachers, T., Meinicke, P., & Igel, C. (2007). Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. International Journal of Neural Systems, 17(5), 369–381.
Müller, M. K., Heinrichs, A., Tewes, A. H. J., Schäfer, A., & , R. P. W. (2007). Similarity rank correlation for face recognition under unenrolled pose. In S. -W. Lee & Li, S. Z. (Eds.), Advances in Biometrics (pp. 67–76). Springer.
Salmen, J., Suttorp, T., Edelbrunner, J., & Igel, C. (2007). Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification. In Proceedings of the IEEE Conference on Hybrid Intelligent Systems (pp. 222–227).
Schlipsing, M. (2007). Echtzeitfähige und robuste Erkennung von Verkehrszeichen in Videosequenzen mit Hilfe von Haar-Merkmalen (Diplomarbeit).
Sharon, D., Jancke, D., Chavane, F., Na′aman, S., & Grinvald, A. (2007). Cortical response field dynamics in cat visual cortex. Cerebral Cortex, 17(12), 2866–2877.
Würtz, R. P. (2007). Organic Computing for Video Analysis. In A. König, Köppen, M., Abraham, A., Igel, C., & Kasabov, N. (Eds.), Seventh International Conference on Hybrid Intelligent Systems, Kaiserslautern, Germany (pp. 6–11). IEEE Computer Society Press.
2006

Pleger, B., Ragert, P., Schwenkreis, P., Forster, A. F., Wilimzig, C., Dinse, H., et al. (2006). Patterns of cortical reorganization parallel impaired tactile discrimination and pain intensity in complex regional pain syndrome. Neuroimage, 32(2), 503–510.
Dinse, H. R., Kleibel, N., Kalisch, T., Ragert, P., Wilimzig, C., & Tegenthoff, M. (2006). Tactile coactivation resets age-related decline of human tactile discrimination. Ann. Neurol., 60(1), 88–94.
Meier, C., Middelanis, J., Wasielewski, B., Neuhoff, S., Roth-Haerer, A., Gantert, M., et al. (2006). Spastic paresis after perinatal brain damage in rats is reduced by human cord blood mononuclear cells. Pediatr. Res., 59(2), 244–249.
Barwiṅski, M., & Würtz, R. P. (2006). A sequence-encoding neural network for face recognition. In M. Verleysen (Ed.), Proceedings of ESANN, Bruges, Belgium (pp. 635–640). d-side publications, Evere, Belgium.
Böhringer, S., Vollmar, T., Tasse, C., Würtz, R. P., Gillessen-Kaesbach, G., Horsthemke, B., & Wieczorek, D. (2006). Syndrome identification based on 2D analysis software. European Journal of Human Genetics, 14(10), 1082–1089. http://doi.org/10.1038/sj.ejhg.5201673
Dinse, H. R. (2006). Cortical reorganization in the aging brain. Prog. Brain Res., 157, 57–80.
Glasmachers, T. (2006). Degeneracy in Model Selection for SVMs with Radial Gaussian Kernel. In M. Verleysen (Ed.), Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN). d-side publications.
Glasmachers, T., & Igel, C. (2006). Maximum-Gain Working Set Selection for Support Vector Machines. Journal of Machine Learning Research, 7, 1437–1466.
Heinrichs, A., Müller, M. K., Tewes, A. H. J., & , R. P. W. (2006). Graphs with Principal Components of Gabor Wavelet Features for Improved Face Recognition. In G. Cristóbal, Javidi, B., & Vallmitjana, S. (Eds.), Information Optics: 5th International Workshop on Information Optics; WIO′06 (pp. 243–252). American Institute of Physics.
Heyden, L., Würtz, R. P., & Peters, G. (2006). Supplementing Bundle Adjustment with Evolutionary Algorithms. In Proceedings of the IET International Conference on Visual Information Engineering 2006 (VIE 2006) (pp. 533–536). Institution of Engineering and Technology.
Kalisch, T., Wilimzig, C., Kleibel, N., Tegenthoff, M., & Dinse, H. R. (2006). Age-related attenuation of dominant hand superiority. PLoS ONE, 1, e90.
Mersch, B., Glasmachers, T., Meinicke, P., & Igel, C. (2006). Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. In Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). Springer-Verlag.
Schmidt, P. A., Maël, E., & Würtz, R. P. (2006). A sensor for dynamic tactile information with applications in human-robot interaction and object exploration. Robotics and Autonomous Systems, 54(12), 1005–1014. http://doi.org/10.1016/j.robot.2006.05.013
Westphal, G., von der Malsburg, C., & Würtz, R. P. (2006). Feature-driven emergence of model graphs for object recognition and categorization. In K. Bellman, Hofmann, P., Müller-Schloer, C., Schmeck, H., & Würtz, R. P. (Eds.), Organic Computing – Controlled Emergence. Internationales Begegnungs- und Forschungszentrum (IBFI), Schloss Dagstuhl, Germany. Retrieved from http://drops.dagstuhl.de/opus/volltexte/2006/575/pdf/06031.WuertzRolf.Paper.575.pdf
2005

Tegenthoff, M., Ragert, P., Pleger, B., Schwenkreis, P., Forster, A. F., Nicolas, V., & Dinse, H. R. (2005). Improvement of tactile discrimination performance and enlargement of cortical somatosensory maps after 5 Hz rTMS. PLoS Biol., 3(11), e362.
Brinkschulte, U., Becker, J., Fey, D., Hochberger, C., Martinetz, T., Müller-Schloer, C., et al. (2005). ARCS 2005 - System Aspects in Organic and Pervasive Computing - Workshops Procedeedings, Innsbruck Austria, March 14-17. VDE Verlag, Berlin, Offenbach.
Glasmachers, T., & Igel, C. (2005). Gradient-based Adaptation of General Gaussian Kernels. Neural Computation, 17(10), 2099–2105.
Tewes, A., Würtz, R. P., & von der Malsburg, C. (2005). A flexible object model for recognising and synthesising facial expressions. In T. Kanade, Ratha, N., & Jain, A. (Eds.), Proceedings of the International Conference on Audio- and Video-based Biometric Person Authentication (pp. 81–90). Springer.
Würtz, R. P. (2005). Organic Computing methods for face recognition. it - Information Technology, 47(4), 207–211. http://doi.org/10.1524/itit.2005.47.4.207
2004

Erlhagen, W., & Jancke, D. (2004). The role of action plans and other cognitive factors in motion extrapolation: A modelling study. Visual Cognition, 11(2-3), 315–340.
Jancke, D., Chavane, F., Naaman, S., & Grinvald, A. (2004). Imaging cortical correlates of illusion in early visual cortex. Nature, 428(6981), 423–426.
Jancke, D., Erlhagen, W., Schöner, G., & Dinse, H. R. (2004). Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex. The Journal of Physiology, 556(3), 971–982.
Krüger, M., Schäfer, A., Tewes, A., & Würtz, R. P. (2004). Communicating agents architecture with applications in multimodal human computer interaction. In P. Dadam & Reichert, M. (Eds.), Informatik 2004 (Vol. 2, pp. 641–645). Gesellschaft für Informatik.
Messer, K., Kittler, J., Sadeghi, M., Hamouz, M., Kostin, A., Cardinaux, F., et al. (2004). Face Authentication Test on the BANCA Database. In Proceedings of ICPR 2004, Cambridge (Vol. 4, pp. 523–532).
Müller-Schloer, C., von der Malsburg, C., & Würtz, R. P. (2004). Aktuelles Schlagwort: Organic Computing. Informatik Spektrum, 27(4), 332–336. http://doi.org/DOI 10.1007/s00287-004-0409-6
Ragert, P., Schmidt, A., Altenmuller, E., & Dinse, H. R. (2004). Superior tactile performance and learning in professional pianists: evidence for meta-plasticity in musicians. Eur. J. Neurosci., 19(2), 473–478.
Westphal, G., & Würtz, R. P. (2004). Fast object and pose recognition through minimum entropy coding. In 17th International Conference on Pattern Recognition (ICPR 2004), Cambridge (Vol. 3, pp. 53–56). IEEE Press. http://doi.org/10.1109/ICPR.2004.1334467
Wundrich, I. J., von der Malsburg, C., & Würtz, R. P. (2004). Image Representation by Complex Cell Responses. Neural Computation, 16(12), 2563–2575. http://doi.org/10.1162/0899766042321760
Würtz, R. P. (2004). Organic Computing for face and object recognition. In P. Dadam & Reichert, M. (Eds.), Informatik 2004 (Vol. 2, pp. 636–640). Gesellschaft für Informatik.
2003

Pleger, B., Foerster, A. F., Ragert, P., Dinse, H. R., Schwenkreis, P., Malin, J. P., et al. (2003). Functional imaging of perceptual learning in human primary and secondary somatosensory cortex. Neuron, 40(3), 643–653.
Dinse, H. R., Ragert, P., Pleger, B., Schwenkreis, P., & Tegenthoff, M. (2003). Pharmacological modulation of perceptual learning and associated cortical reorganization. Science, 301(5629), 91–94.
Loos, H. S., Wieczorek, D., Würtz, R. P., von der Malsburg, C., & Horsthemke, B. (2003). Computer-based recognition of dysmorphic faces. European Journal of Human Genetics, 11, 555–560. http://doi.org/10.1038/sj.ejhg.5200997
Lourens, T., & Würtz, R. P. (2003). Extraction and Matching of Symbolic Contour Graphs. International Journal of Pattern Recognition and Artificial Intelligence, 17(7), 1279–1302. http://doi.org/10.1142/S0218001403002848
Prodöhl, C., Würtz, R. P., & von der Malsburg, C. (2003). Learning the Gestalt Rule of Collinearity from Object Motion. Neural Computation, 15(8), 1865–1896. http://doi.org/10.1162/08997660360675071
Schmidt, P., Maël, E., & Würtz, R. P. (2003). European Patent Number: EP 1 142 118 B1 Tastsensor. Europäisches Patentamt, München.
Schmidt, P., Maël, E., & Würtz, R. P. (2003). US Patent Number: 6 593 756 Tactile sensor. United States Patent and Trademark Office.
Würtz, R. P. (2003). Conference Report: 4th Workshop on Dynamic Perception. KI - Künstliche Intelligenz, 17(2), 38.
2002

Godde, B., Berkefeld, T., David-Jurgens, M., & Dinse, H. R. (2002). Age-related changes in primary somatosensory cortex of rats: evidence for parallel degenerative and plastic-adaptive processes. Neurosci Biobehav Rev, 26(7), 743–752.
Li, S. C., & Dinse, H. R. (2002). Aging of the brain, sensorimotor, and cognitive processes. Neurosci Biobehav Rev, 26(7), 729–732.
Würtz, R. P., & Lappe_(eds.), M. (2002). Dynamic Perception. infix Verlag/IOS press, Berlin, Amsterdam.
Godde, B., Leonhardt, R., Cords, S. M., & Dinse, H. R. (2002). Plasticity of orientation preference maps in the visual cortex of adult cats. Proc. Natl. Acad. Sci. U.S.A., 99(9), 6352–6357.
Dinse, H. R., & Böhmer, G. (2002). Plastic-adaptive properties of cortical areas . In A. Schüz & Miller, R. (Eds.), Cortical Areas: Unity and Diversity: Conceptual Advances in Brain Research (pp. 311–348). London : Taylor & Francis .
Dinse, H. R., & Merzenich, M. M. (2002). Adaptation of Inputs in the Somatosensory System . In M. Fahle & Poggio, T. (Eds.), Perceptual Learning (pp. 19–42). : MIT Press .
Dinse, H. R., & Schreiner, C. E. (2002). Do primary sensory areas play homologous roles in different sensory modalities? . In A. Schüz & Miller, R. (Eds.), Cortical Areas: Unity and Diversity: Conceptual Advances in Brain Research (pp. 273–310). London : Taylor & Francis .
Heinrichs, A., Eckes, C., Würtz, R. P., & von der Malsburg, C. (2002). Statistical Learning of the Detection of Faces in Natural Images. In R. P. Würtz & Lappe, M. (Eds.), Dynamic Perception (pp. 265–270). infix Verlag/IOS press.
Igel, C., von Seelen, W., Erlhagen, W., & Jancke, D. (2002). Evolving field models for inhibition effects in early vision. Neurocomputing, 44, 467–472.
Lücke, J., von der Malsburg, C., & Würtz, R. P. (2002). Macrocolumns as decision units. In J. R. Dorronsoro (Ed.), Artificial Neural Networks - ICANN 2002, Madrid (Vol. 2415, pp. 57–62). Springer.
Wieghardt, J., Würtz, R. P., & von der Malsburg, C. (2002). Gabor-based Feature Point Tracking with Automatically Learned Constraints. In R. P. Würtz & Lappe, M. (Eds.), Dynamic Perception (pp. 121–126). infix Verlag/IOS press.
Wieghardt, J., Würtz, R. P., & von der Malsburg, C. (2002). Learning the Topology of Object Views. In A. Heyden, Sparr, G., Nielsen, M., & Johansen, P. (Eds.), Computer Vision - ECCV 2002 (p. IV-747-IV-760). Springer.
Wundrich, I. J., von der Malsburg, C., & Würtz, R. P. (2002). Image Reconstruction from Gabor Magnitudes. In H. H. Bülthoff, Lee, S. -W., Poggio, T. A., & Wallraven, C. (Eds.), Biologically Motivated Computer Vision (pp. 117–126). Springer.
Würtz, R. P. (2002). Face Recognition, Neurophysiology, and Neural technology. In M. A. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks (2.nd ed., pp. 434–437). MIT Press.
Würtz, R. P. (2002). Technik und Leistungsfähigkeit automatischer Gesichtserkennung. FIfF-Kommunikation, 19(1), 27–30.
Würtz, R. P. (2002). Vision and Touch for Grasping. In G. D. Hager, Christensen, H. I., Bunke, H., & Klein, R. (Eds.), Sensor Based Intelligent Robots (pp. 74–86). Springer.
2001

Pleger, B., Dinse, H. R., Ragert, P., Schwenkreis, P., Malin, J. P., & Tegenthoff, M. (2001). Shifts in cortical representations predict human discrimination improvement. Proc. Natl. Acad. Sci. U.S.A., 98(21), 12255–12260.
Dinse, H. R., & Jancke, D. (2001). Chapter 10: Comparative population analysis of cortical representations in parametric spaces of visual field and skin : a unifying role for nonlinear interactions as a basis for active information processing across modalities. In M. A. L. Nicolelis (Ed.), Advances in neural population coding (pp. 155–173). Elsevier.
Dinse, H. R., & Jancke, D. (2001). Comparative population analysis of cortical representations in parametric spaces of visual field and skin: A unifying role for nonlinear interactions as a basis for active information processing across modalities. Progress in brain research, 130, 155–173.
Dinse, H. R., & Jancke, D. (2001). Time-variant processing in V1: From microscopic (single cell) to mesoscopic (population) levels. Trends in neurosciences, 24(4), 203–205.
Igel, C., Erlhagen, W., & Jancke, D. (2001). Optimization of dynamic neural fields. Neurocomputing, 36(1), 225–233.
König, P., Kayser, C., Bonin, V., & Würtz, R. P. (2001). Efficient evaluation of serial sections by iterative Gabor matching. Journal of Neuroscience Methods, 111(2), 141–150. http://doi.org/10.1016/S0165-0270(01)00439-3
Würtz, R. P. (2001). Gabor phase space molecules for image understanding. In I. Wundrich (Ed.), The Mathematical, Computational and Biological Study of Vision (p. 23).
2000

Jancke, D. (2000). Orientation formed by a spot’s trajectory: A two-dimensional population approach in primary visual cortex. J Neurosci, 20(14), U13–U18.
Würtz, R. P. (2000). Gossiping Nets. Artificial Intelligence, 119(1-2), 295–299.
Würtz, R. P., & Lourens, T. (2000). Corner detection in color images through a multiscale combination of end-stopped cortical cells. Image and Vision Computing, 18(6-7), 531–541.
1999

Becker, M., Kefalea, E., Maël, E., von der Malsburg, C., Pagel, M., Triesch, J., et al. (1999). GripSee: A Gesture-controlled Robot for Object Perception and Manipulation. Autonomous Robots, 6(2), 203–221. http://doi.org/10.1023/A:1008839628783
Becker, M., Kefalea, E., Maël, E., von der Malsburg, C., Pagel, M., Triesch, J., et al. (1999). GripSee: A Gesture-controlled Robot for Object Perception and Manipulation. Autonomous Robots, 6(2), 203–221. http://doi.org/10.1023/A:1008839628783
Erlhagen, W., Bastian, A., Jancke, D., Riehle, A., & Schöner, G. (1999). The distribution of neuronal population activation (DPA) as a tool to study interaction and integration in cortical representations. Journal of Neuroscience Methods, 94(1), 53–66.
Jancke, D., Erlhagen, W., Dinse, H. R., Akhavan, A. C., Giese, M., Steinhage, A., & Schöner, G. (1999). Parametric population representation of retinal location: Neuronal interaction dynamics in cat primary visual cortex. J Neurosci, 19(20), 9016–9028.
Kefalea, E., Maël, E., & Würtz, R. P. (1999). An Integrated Object Representation for Recognition and Grasping. In L. C. Jain (Ed.), Proceedings of the Third International Conference on Knowledge-based Intelligent Information Engineering Systems, Adelaide, Australia (pp. 423–426). IEEE Press.
Würtz, R. P. (1999). Neural networks as a model for visual perception: what is lacking? Cognitive Systems, 5(2), 103–112.
Würtz, R. P., Konen, W., & Behrmann, K. -O. (1999). On the performance of neuronal matching algorithms. Neural Networks, 12(1), 127–134. http://doi.org/10.1016/S0893-6080(98)00112-9
1998

Lourens, T., & Würtz, R. P. (1998). Object Recognition by matching symbolic edge graphs. In R. Chin & Pong, T. -C. (Eds.), Computer Vision – ACCV′98 (Vol. 1352, p. II-193 - II-200). Springer Verlag. http://doi.org/10.1016/S0262-8856(99)00061-X
Würtz, R. P. (1998). Biologically Inspired Methods for Model Matching and Object Recognition. In Y. Sawada (Ed.), Proceedings of the 2nd R.I.E.C. International Symposium on Design and Architecture of Information Processing Systems Based on the Brain Information Principles, in Sendai, Japan, March 16-18, 1998 (pp. 101–106).
1997

McKenna, S. J., Gong, S., Würtz, R. P., Tanner, J., & Banin, D. (1997). Tracking Facial Feature Points with Gabor Wavelets and Shape Models. In J. Bigün, Chollet, G., & Borgefors, G. (Eds.), Proceedings of the First International Conference on Audio- and Video-based Biometric Person Authentication (Vol. 1206, pp. 35–42). Springer.
Würtz, R. P. (1997). Context dependent feature groups, a proposal for object representation. Behavioral and Brain Sciences, 20(4), 702–703. http://doi.org/10.1017/S0140525X97441602
Würtz, R. P. (1997). Neuronal theories and technical systems for face recognition. In M. Verleysen (Ed.), Proceedings of the Fifth European Symposium On Artificial Neural Networks, Bruges (Belgium), 16-18 April 1997 (pp. 73–78). D facto, Brussels.
Würtz, R. P. (1997). Object recognition robust under translations, deformations and changes in background. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7), 769–775. http://doi.org/10.1109/34.598234
Würtz, R. P., & Lourens, T. (1997). Corner detection in color images by multiscale combination of end-stopped cortical cells. In W. Gerstner, Germond, A., Hasler, M., & Nicoud, J. -D. (Eds.), Artificial Neural Networks - ICANN ′97 (Vol. 1327, pp. 901–906). Springer Verlag.
1996

Würtz, R. P., Konen, W., & Behrmann, K. -O. (1996). How fast can neuronal algorithms match patterns? In C. von der Malsburg, Vorbrüggen, J. C., von Seelen, W., & Sendhoff, B. (Eds.), Artificial Neural Networks - ICANN 96 (Vol. 1112, pp. 145–150). Springer Verlag.
1995

Würtz, R. P. (1995). Building visual correspondence maps – from neural dynamics to a face recognition system. In R. Moreno-Díaz & Mira-Mira, J. (Eds.), Brain Processes, Theories and Models (pp. 420–429). MIT Press.
Konen, W., Vorbrüggen, J. C., & Würtz, R. P. (1995). Patent Nummer 4406020: Verfahren zur automatisierten Erkennung von Objekten. Deutsches Patentamt, München.
Schöner, G., Dose, M., & Engels, C. (1995). Dynamics of behavior: Theory and applications for autonomous robot architectures. Robotics and Autonomous Systems, 16, 213–245.
Würtz, R. P. (1995). Multilayer Dynamic Link Networks for Establishing Image Point Correspondences and Visual Object Recognition (p. 155). Thun, Frankfurt am Main: Verlag Harri Deutsch.
1994

Würtz, R. P., & von der Malsburg, C. (1994). Image Point Correspondences from a Wavelet Representation and a Hierarchical Dynamic Link Network. In T. Smithers & Moreno, A. (Eds.), The Role of Dynamics and Representation in Adaptive Behavior and Cognition (pp. 200–202).
1993

Lades, M., Vorbrüggen, J. C., Buhmann, J., Lange, J., von der Malsburg, C., Würtz, R. P., & Konen, W. (1993). Distortion Invariant Object Recognition in the Dynamic Link Architecture. IEEE Transactions on Computers, 42(3), 300–311. http://doi.org/10.1109/12.210173
1992

Würtz, R. P. (1992). Gesichtserkennung mit dynamischen neuronalen Netzen. Spektrum der Wissenschaft, 18–22.
Buhmann, J., Lange, J., von der Malsburg, C., Vorbrüggen, J. C., & Würtz, R. P. (1992). Object Recognition with Gabor Functions in the Dynamic Link Architecture – Parallel Implementation on a Transputer Network. In B. Kosko (Ed.), Neural Networks for Signal Processing (pp. 121–159). Prentice Hall, Englewood Cliffs, NJ.
Doursat, R., Konen, W., Lades, M., von der Malsburg, C., Vorbrüggen, J., Wiskott, L., & Würtz, R. (1992). Neural Mechanisms of Elastic Pattern Matching. In M. van der Meer (Ed.), Statusseminar des BMFT: Neuroinformatik (pp. 71–82). Projektträger Informationstechnik/DLR, Berlin.
1991

Lades, M., Vorbrüggen, J. C., & Würtz, R. P. (1991). Recognizing Faces with a Transputer farm. In T. S. Durrani, Sandham, W. A., Soraghan, J. J., & Forbes, S. M. (Eds.), Applications of Transputers~3 (pp. 148–153). IOS Press; Amsterdam, Oxford, Washington, Tokio.
von der Malsburg, C., Würtz, R. P., & Vorbrüggen, J. C. (1991). Bilderkennung mit dynamischen Neuronennetzen. In W. Brauer & Hernández, D. (Eds.), Verteilte Künstliche Intelligenz und kooperatives Arbeiten (pp. 519–529). Springer.
Würtz, R. P., Vorbrüggen, J. C., von der Malsburg, C., & Lange, J. (1991). A Transputer-based Neural Object Recognition System. In H. Burkhardt, Neuvo, Y., & Simon, J. C. (Eds.), From Pixels to Features II - Parallelism in Image Processing (pp. 275–294). North Holland, Amsterdam.
1990

Würtz, R. P., Vorbrüggen, J. C., & von der Malsburg, C. (1990). A Transputer System for the Recognition of Human Faces by Labeled Graph Matching. In R. Eckmiller, Hartmann, G., & Hauske, G. (Eds.), Parallel Processing in Neural Systems and Computers (pp. 37–41). North Holland, Amsterdam.
1986

Schöner, G., Haken, H., & Kelso, J. A. S. (1986). A stochastic theory of phase transitions in human hand movement. Biological Cybernetics, 53, 247–257.