Matching recall and storage in sequence learning with spiking neural networks J Brea, W Senn, JP Pfister Journal of neuroscience 33 (23), 9565-9575, 2013 | 99 | 2013 |

Eligibility traces and plasticity on behavioral time scales: experimental support of neohebbian three-factor learning rules W Gerstner, M Lehmann, V Liakoni, D Corneil, J Brea Frontiers in neural circuits 12, 53, 2018 | 78 | 2018 |

Algorithmic Composition of Melodies with Deep Recurrent Neural Networks F Colombo, SP Muscinelli, A Seeholzer, J Brea, W Gerstner arXiv preprint arXiv:1606.07251, 2016 | 41 | 2016 |

Sequence learning with hidden units in spiking neural networks J Brea, W Senn, JP Pfister Advances in neural information processing systems 24, 1422-1430, 2011 | 41 | 2011 |

Prospective coding by spiking neurons J Brea, AT Gaál, R Urbanczik, W Senn PLoS computational biology 12 (6), e1005003, 2016 | 28 | 2016 |

Biologically plausible deep learning—But how far can we go with shallow networks? B Illing, W Gerstner, J Brea Neural Networks 118, 90-101, 2019 | 27 | 2019 |

Efficient model-based deep reinforcement learning with variational state tabulation D Corneil, W Gerstner, J Brea International Conference on Machine Learning, 1049-1058, 2018 | 25 | 2018 |

A normative theory of forgetting: lessons from the fruit fly J Brea, R Urbanczik, W Senn PLoS Comput Biol 10 (6), e1003640, 2014 | 22 | 2014 |

Does computational neuroscience need new synaptic learning paradigms? J Brea, W Gerstner Current Opinion in Behavioral Sciences 11, 61-66, 2016 | 19 | 2016 |

Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity T Mesnard, W Gerstner, J Brea arXiv preprint arXiv:1612.03214, 2016 | 11 | 2016 |

GaussianProcesses. jl: A Nonparametric Bayes package for the Julia Language J Fairbrother, C Nemeth, M Rischard, J Brea, T Pinder arXiv preprint arXiv:1812.09064, 2018 | 7 | 2018 |

Is prioritized sweeping the better episodic control? J Brea arXiv preprint arXiv:1711.06677, 2017 | 7 | 2017 |

Decoupling Backpropagation using Constrained Optimization Methods A Gotmare, V Thomas, J Brea, M Jaggi | 6 | 2018 |

Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape J Brea, B Simsek, B Illing, W Gerstner arXiv preprint arXiv:1907.02911, 2019 | 5 | 2019 |

Learning in Volatile Environments With the Bayes Factor Surprise V Liakoni, A Modirshanechi, W Gerstner, J Brea Neural Computation 33 (2), 269-340, 2021 | 4* | 2021 |

On the choice of metric in gradient-based theories of brain function SC Surace, JP Pfister, W Gerstner, J Brea PLOS Computational Biology 16 (4), e1007640, 2020 | 4 | 2020 |

Learning to Generate Music with BachProp F Colombo, J Brea, W Gerstner arXiv preprint arXiv:1812.06669, 2018 | 2 | 2018 |

Exponentially long orbits in Hopfield neural networks SP Muscinelli, W Gerstner, J Brea Neural computation 29 (2), 458-484, 2017 | 2 | 2017 |

Testing two competing hypotheses for Eurasian jays’ caching for the future P Amodio, J Brea, BG Farrar, L Ostojić, NS Clayton Scientific Reports 11 (1), 1-15, 2021 | | 2021 |

Neurons that Remember How We Got There W Senn, J Brea Neuron 85 (4), 664-666, 2015 | | 2015 |