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Communications Biology|March 4, 2021
Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networksJannik Luboeinski, Christian TetzlaffNetwork Neuroscience (Cambridge, Mass.)|March 14, 2020
The self-organized learning of noisy environmental stimuli requires distinct phases of plasticitySteffen Krüppel, Christian TetzlaffFrontiers in Computational Neuroscience|December 15, 2010
Closed-Form Treatment of the Interactions between Neuronal Activity and Timing-Dependent Plasticity in Networks of Linear NeuronsChristoph Kolodziejski, Christian Tetzlaff, Florentin WörgötterCell Reports Methods|September 19, 2025
The Brownian dynamics simulator PyRID for reacting and interacting particles written in PythonMoritz Becker, Nahid Safari, Christian TetzlaffFrontiers in Neurorobotics|April 6, 2017
Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion ControlTimo Nachstedt, Christian Tetzlaff, Poramate ManoonpongPlos Computational Biology|March 5, 2024
Unsupervised learning of perceptual feature combinationsMinija Tamosiunaite, Christian Tetzlaff, Florentin WörgötterFrontiers in Computational Neuroscience|May 29, 2019
A Theoretical Framework to Derive Simple, Firing-Rate-Dependent Mathematical Models of Synaptic PlasticityJanne Lappalainen, Juliane Herpich, Christian TetzlaffNeural Networks : the Official Journal of the International Neural Network Society|December 25, 2019
Evolving artificial neural networks with feedbackSebastian Herzog, Christian Tetzlaff, Florentin WörgötterPlos One|August 26, 2016
Induction and Consolidation of Calcium-Based Homo- and Heterosynaptic Potentiation and DepressionYinyun Li, Tomas Kulvicius, Christian TetzlaffPlos Computational Biology|March 22, 2021
The biophysical basis underlying the maintenance of early phase long-term potentiationMoritz F P Becker, Christian TetzlaffPageof 5