| Triplets of spikes in a model of spike timing-dependent plasticity JP Pfister, W Gerstner Journal of Neuroscience 26 (38), 9673-9682, 2006 | 787 | 2006 |
| Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning JP Pfister, T Toyoizumi, D Barber, W Gerstner Neural computation 18 (6), 1318-1348, 2006 | 312 | 2006 |
| A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations J Gjorgjieva, C Clopath, J Audet, JP Pfister Proceedings of the national academy of sciences 108 (48), 19383-19388, 2011 | 239 | 2011 |
| Generalized Bienenstock–Cooper–Munro rule for spiking neurons that maximizes information transmission T Toyoizumi, JP Pfister, K Aihara, W Gerstner Proceedings of the National Academy of Sciences 102 (14), 5239-5244, 2005 | 164 | 2005 |
| Nerve injury-induced neuropathic pain causes disinhibition of the anterior cingulate cortex SM Blom, JP Pfister, M Santello, W Senn, T Nevian Journal of Neuroscience 34 (17), 5754-5764, 2014 | 158 | 2014 |
| 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 | 137 | 2013 |
| Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials JP Pfister, P Dayan, M Lengyel Nature neuroscience 13 (10), 1271-1275, 2010 | 93 | 2010 |
| Synaptic plasticity as Bayesian inference L Aitchison, J Jegminat, JA Menendez, JP Pfister, A Pouget, PE Latham Nature neuroscience 24 (4), 565-571, 2021 | 84 | 2021 |
| Optimality model of unsupervised spike-timing-dependent plasticity: synaptic memory and weight distribution T Toyoizumi, JP Pfister, K Aihara, W Gerstner Neural computation 19 (3), 639-671, 2007 | 68 | 2007 |
| STDP in oscillatory recurrent networks: theoretical conditions for desynchronization and applications to deep brain stimulation JP Pfister, PA Tass Frontiers in computational neuroscience 4, 2010 | 59 | 2010 |
| Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception A Kutschireiter, SC Surace, H Sprekeler, JP Pfister Scientific reports 7 (1), 8722, 2017 | 57 | 2017 |
| Sequence learning with hidden units in spiking neural networks J Brea, W Senn, JP Pfister Advances in neural information processing systems 24, 2011 | 55 | 2011 |
| How to avoid the curse of dimensionality: Scalability of particle filters with and without importance weights SC Surace, A Kutschireiter, JP Pfister SIAM review 61 (1), 79-91, 2019 | 51 | 2019 |
| Spike-timing dependent plasticity and mutual information maximization for a spiking neuron model T Toyoizumi, JP Pfister, K Aihara, W Gerstner Advances in neural information processing systems 17, 2004 | 46 | 2004 |
| STDP in adaptive neurons gives close-to-optimal information transmission G Hennequin, W Gerstner, JP Pfister Frontiers in Computational Neuroscience 4, 143, 2010 | 42 | 2010 |
| Denoising normalizing flow C Horvat, JP Pfister Advances in Neural Information Processing Systems 34, 9099-9111, 2021 | 36 | 2021 |
| Beyond pair-based STDP: A phenomenological rule for spike triplet and frequency effects JP Pfister, W Gerstner Advances in neural information processing systems 18, 2005 | 36 | 2005 |
| Online maximum-likelihood estimation of the parameters of partially observed diffusion processes SC Surace, JP Pfister IEEE transactions on automatic control 64 (7), 2814-2829, 2018 | 31 | 2018 |
| Optimal hebbian learning: A probabilistic point of view JP Pfister, D Barber, W Gerstner International Conference on Artificial Neural Networks, 92-98, 2003 | 30 | 2003 |
| The Hitchhiker’s guide to nonlinear filtering A Kutschireiter, SC Surace, JP Pfister Journal of Mathematical Psychology 94, 102307, 2020 | 26 | 2020 |
Taro ToyoizumiRIKEN Center for Brain ScienceVerifisert e-postadresse på riken.jp
