Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences

Wörgötter, Florentin, Prof. Dr.

  • 1988 -1990 Postdoctoral Research Fellow, CNS Program, Prof. Dr. Koch, Div. of Biology 216-76, CALTECH, Pasadena, USA.
  • 1990 - 1995 Assistant at the Ruhr-Universität Bochum, Institut f. Physiologie, Prof. Dr. Eysel, Bochum, FRG.
  • 1994 Visiting Professor at the Academia Sinica, Inst. of Biophysics, Prof. Dr. Diao, Beijing, China.
  • 1995 - 2000 Heisenberg Fellow at the Ruhr-Universität Bochum, Institut f. Physiologie.
  • 1997 - 1997 Visiting Professor at the KTH, Stockholm, NADA-SANS, Prof. A. Lansner, Sweden.
  • 2000 Professor (“apl.”) at the Medical School in Bochum
  • 2000-2005 Professor at the Dept. of Psychology, Univ. Stirling, Scotland
  • 2002-2005 Director of INCITE (Institute of Neuronal Computational Intelligence & Technology)
  • since 2005 Professor at the Bernstein Center of University of Göttingen, Germany

Major Research Interests

Computational neuroscience, Artificial Neural Network, Experimental Neuroscience, Temporal Sequence Learning, Models of Synaptic Plasticity, The visual System and its Functional Connectivity

Homepage Department/Research Group


Selected Recent Publications

  • Aksoy EE, Wörgötter F (2017). Semantic decomposition and recognition of long and complex manipulation action sequences. International Journal of Computer Vision 122(1): 84-115.

  • Fauth M, Wörgötter F, Tetzlaff C (2015). Formation and Maintenance of Robust Long-Term Information Storage in the Presence of Synaptic Turnover. PLoS Computational Biology 11(12): e1004684.

  • Tetzlaff C, Dasgupta S, Kulvicius T, Wörgötter F (2015). The use of hebbian cell assemblies for nonlinear computation. Scientific Reports 5: 12866.

  • Tetzlaff C, Kolodziejski C, Timme M, Tsodyks M, Wörgötter F (2013). Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation. PLoS Computational Biology 9(10): e1003307.

  • Wörgötter F, Aksoy EE, Krüger N, Piater J, Ude A, Tamosiunaite M (2013). A Simple Ontology of Manipulations: Towards representations for manipulation actions in robotics. IEEE Transactions on Autonomous Mental Development 5(2): 117-34.

  • Kulvicius, T., Ning, K., Tamosiunaite, M. and Wörgötter, F. (2012) Joining movement sequences: Modified dynamic movement primitives for robotics applications exemplified on handwriting. IEEE Trans. on Robotics (IEEE T-RO) 28(1), 145-157.

  • Tetzlaff C, Kolodziejski, C , Timme, M. and Wörgötter F. (2011) Synaptic Scaling in Combination with many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity. Frontiers in Comp. Neurosci. 5, 47. doi:10.3389/fncom.2011.00047.

  • Steingrube, S.; Timme, M.; Wörgötter, F. and Manoonpong, P. (2010) Self-Organized Adaptation of Simple Neural Circuits Enables Complex Robot Behavior. Nature Physics (Article) 6, 224-230. doi:10.1038/nphys1508.

  • Porr, B. and Wörgötter, F. (2009). Learning with 'relevance': Using a third factor to stabilize Hebbian learning. Neural Comp.21(10): 2990.

  • Manoonpong P, Geng T, Kulvicius T, Porr B, Wörgötter F (2007) Adaptive, Fast Walking in a Biped Robot under Neuronal Control and Learning. PLoS Comput Biol 3(7): e134.

  • Tamosiunaite, M., Porr, B. and Wörgötter, F. (2007) Self-influencing plasticity: Recurrent changes of synaptic weights can lead to specific functional properties. Comp. Neurosci. (in press, doi:10.1007/s10827-007-0021-2)

  • Porr, B., and Wörgötter, F. (2006). Strongly improved stability and faster convergence of temporal sequence learning by utilising input correlations only. Neural Comp. 18(6), 1380-1412.

  • Geng, T., Porr, B. and Wörgötter, F. (2006), Coupling of neural computation with physical computation for stable dynamic biped walking control, Neural Comp. 18(5), 1156-1196