| Self-organized criticality in developing neuronal networks C Tetzlaff, S Okujeni, U Egert, F Wörgötter, M Butz PLoS Comput. Biol 6 (12), e1001013, 2010 | 231 | 2010 |
| Opposing Effects of Neuronal Activity on Structural Plasticity M Fauth, C Tetzlaff Frontiers in Neuroanatomy 10, 75, 2016 | 113 | 2016 |
| Time scales of memory, learning, and plasticity C Tetzlaff, C Kolodziejski, I Markelic, F Wörgötter Biological cybernetics 106 (11), 715-726, 2012 | 104 | 2012 |
| Synaptic scaling in combination with many generic plasticity mechanisms stabilizes circuit connectivity C Tetzlaff, C Kolodziejski, M Timme, F Wörgötter Frontiers in computational neuroscience 5, 47, 2011 | 96 | 2011 |
| Evolving artificial neural networks with feedback S Herzog, C Tetzlaff, F Wörgötter Neural Networks 123, 153-162, 2020 | 83* | 2020 |
| The Formation of Multi-synaptic Connections by the Interaction of Synaptic and Structural Plasticity and Their Functional Consequences. M Fauth, F Wörgötter, C Tetzlaff PLoS computational biology 11 (1), e1004031, 2015 | 80 | 2015 |
| Synaptic scaling enables dynamically distinct short- and long-term memory formation C Tetzlaff, C Kolodziejski, M Timme, M Tsodyks, F Wörgötter PLoS Computational Biology 9 (10), e1003307, 2013 | 58 | 2013 |
| Emulating dendritic computing paradigms on analog neuromorphic hardware J Kaiser, S Billaudelle, E Müller, C Tetzlaff, J Schemmel, S Schmitt Neuroscience 489, 290-300, 2022 | 43 | 2022 |
| CA2 beyond social memory: Evidence for a fundamental role in hippocampal information processing AB Lehr, A Kumar, C Tetzlaff, T Hafting, M Fyhn, TM Stöber Neuroscience & Biobehavioral Reviews 126, 398-412, 2021 | 41 | 2021 |
| Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control T Nachstedt, C Tetzlaff, P Manoonpong Frontiers in Neurorobotics 11, 14, 2017 | 41 | 2017 |
| Formation and maintenance of robust long-term information storage in the presence of synaptic turnover M Fauth, F Wörgötter, C Tetzlaff PLoS Comput Biol 11 (12), e1004684, 2015 | 37 | 2015 |
| The Use of Hebbian Cell Assemblies for Nonlinear Computation C Tetzlaff, S Dasgupta, T Kulvicius, F Wörgötter Scientific Reports 5, 2015 | 37 | 2015 |
| Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot E Grinke, C Tetzlaff, F Wörgötter, P Manoonpong Frontiers in neurorobotics 9, 11, 2015 | 36 | 2015 |
| Analysis of synaptic scaling in combination with hebbian plasticity in several simple networks C Tetzlaff, C Kolodziejski, M Timme, F Wörgötter Frontiers in computational neuroscience 6, 2012 | 30 | 2012 |
| Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs T Nachstedt, C Tetzlaff Scientific Reports 7, 2017 | 27 | 2017 |
| Modeling the shape of synaptic spines by their actin dynamics M Bonilla-Quintana, F Wörgötter, C Tetzlaff, M Fauth Frontiers in synaptic neuroscience 12, 9, 2020 | 23 | 2020 |
| Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks J Luboeinski, C Tetzlaff Communications Biology 4 (1), 1-17, 2021 | 21 | 2021 |
| Principles underlying the input-dependent formation and organization of memories J Herpich, C Tetzlaff Network Neuroscience 3 (2), 606-634, 2019 | 18 | 2019 |
| Robust trajectory generation for robotic control on the neuromorphic research chip Loihi C Michaelis, AB Lehr, C Tetzlaff Frontiers in Neurorobotics 14, 97, 2020 | 16 | 2020 |
| Induction and Consolidation of Calcium-Based Homo-and Heterosynaptic Potentiation and Depression Y Li, T Kulvicius, C Tetzlaff PloS one 11 (8), e0161679, 2016 | 15 | 2016 |
