Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und Molekulare Biowissenschaften

Dr. Christian Tetzlaff


  • 2009 Diplom in Physics, Georg August University, Göttingen
  • 2010-2013 Max Planck Institute for Dynamics and Self-Organization / University of Göttingen / GGNB program Physics of Biological and Complex Systems
  • 2013 Dissertation in Physics (Dr.rer.nat.), Georg August University, Göttingen
  • Since 2015 Bernstein Fellow (independent research position) at the Max Planck Institute for Dynamics and Self-Organization, Göttingen and the University of Göttingen




Major Research Interests


    The central goal of my research is to understand the interactions of adaptive dynamics on different time scales in neuronal systems and the related emergence of complex behaviors in closed-loop scenarios. In more detail, my group analyses with analytical and numerical tools the interactions of different, experimentally well-known plasticity mechanisms depending on environmental stimuli and their relations to cognitive processes as learning, computation, and memory formation which serve as the basis of complex behaviors. Thereby, one important part of my research is to assess experimentally testable predictions and to transfer the analyzed mechanisms and behaviors to robotic platforms and biological experiments for testing hypothesized functions in real-world, closed-loop scenarios.



Homepage Department/Research Group
http://www.bccn-goettingen.de/dr-christian-tetzlaff




Selected Recent Publications


  • Tetzlaff C, Dasgupta S, Kulvicius T, Wörgötter F (2015). The use of hebbian cell assemblies for nonlinear computation. Scientific Reports, 5:12866.
  • 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.
  • Fauth M, Wörgötter F, Tetzlaff C (2015). The formation of multi-synaptic connections by the interaction of synaptic and structural plasticity and their functional consequences. PLoS Computational Biology, 11(1):e1004031.
  • 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), e10003307
  • Tetzlaff C, Kolodziejski C, Timme M, Wörgötter F (2011). Synaptic Scaling in combination with many generic plasticity mechanisms stabilizes circuit connectivity. Frontiers in Computational Neuroscience, 5:47.
  • Tetzlaff C, Okujeni S, Egert U, Wörgötter F, Butz M (2010). Self-organized criticality in developing neuronal networks. PLoS Computational Biology, 6(12):e1001013.