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Neural Computation|October 25, 2017
Balancing New against Old Information: The Role of Puzzlement Surprise in LearningMohammadjavad Faraji, Kerstin Preuschoff, Wulfram GerstnerCurrent Opinion in Neurobiology|April 22, 2017
The temporal paradox of Hebbian learning and homeostatic plasticityFriedemann Zenke, Wulfram Gerstner, Surya GanguliChaos (Woodbury, N.Y.)|July 11, 2006
Statistics of subthreshold neuronal voltage fluctuations due to conductance-based synaptic shot noiseMagnus J E Richardson, Wulfram GerstnerNeural Networks : the Official Journal of the International Neural Network Society|June 30, 2019
Biologically plausible deep learning - But how far can we go with shallow networks?Bernd Illing, Wulfram Gerstner, Johanni BreaNature Neuroscience|August 18, 2009
Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learningGediminas Luksys, Wulfram Gerstner, Carmen SandiPlos Computational Biology|July 7, 2018
Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagationHesam Setareh, Moritz Deger, Wulfram GerstnerPlos Computational Biology|November 19, 2013
Synaptic plasticity in neural networks needs homeostasis with a fast rate detectorFriedemann Zenke, Guillaume Hennequin, Wulfram GerstnerFrontiers in Computational Neuroscience|December 5, 2019
Optimal Stimulation Protocol in a Bistable Synaptic Consolidation ModelChiara Gastaldi, Samuel Muscinelli, Wulfram GerstnerPlos Computational Biology|October 1, 2016
Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field FormationCarlos S N Brito, Wulfram GerstnerNature Communications|April 22, 2015
Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networksFriedemann Zenke, Everton J Agnes, Wulfram GerstnerPageof 22