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Henning Sprekeler - Publications

Affiliations: 
University of Cambridge, Cambridge, England, United Kingdom 
Area:
Computational Neuroscience
Website:
http://learning.eng.cam.ac.uk/Public/Sprekeler/WebHome
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42 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2021 Remme MWH, Bergmann U, Alevi D, Schreiber S, Sprekeler H, Kempter R. Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation. Plos Computational Biology. 17: e1009681. PMID 34874938 DOI: 10.1371/journal.pcbi.1009681  0.744
2021 Vercruysse F, Naud R, Sprekeler H. Self-organization of a doubly asynchronous irregular network state for spikes and bursts. Plos Computational Biology. 17: e1009478. PMID 34748532 DOI: 10.1371/journal.pcbi.1009478  0.768
2020 Hertäg L, Sprekeler H. Learning prediction error neurons in a canonical interneuron circuit. Elife. 9. PMID 32820723 DOI: 10.7554/eLife.57541  0.313
2020 Naumann LB, Sprekeler H. Presynaptic inhibition rapidly stabilises recurrent excitation in the face of plasticity. Plos Computational Biology. 16: e1008118. PMID 32764742 DOI: 10.1371/journal.pcbi.1008118  0.4
2020 Hertäg L, Sprekeler H. Author response: Learning prediction error neurons in a canonical interneuron circuit Elife. DOI: 10.7554/Elife.57541.Sa2  0.328
2019 Hertäg L, Sprekeler H. Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types. Plos Computational Biology. 15: e1006999. PMID 31095556 DOI: 10.1371/journal.pcbi.1006999  0.366
2018 Naud R, Sprekeler H. Sparse bursts optimize information transmission in a multiplexed neural code. Proceedings of the National Academy of Sciences of the United States of America. PMID 29934400 DOI: 10.1073/pnas.1720995115  0.762
2018 Weber SN, Sprekeler H. Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity. Elife. 7. PMID 29465399 DOI: 10.7554/eLife.34560  0.369
2018 Weber SN, Sprekeler H. Author response: Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity Elife. DOI: 10.7554/Elife.34560.037  0.349
2017 Kutschireiter A, Surace SC, Sprekeler H, Pfister JP. Publisher Correction: Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception. Scientific Reports. 7: 17585. PMID 29229925 DOI: 10.1038/S41598-017-17246-9  0.562
2017 Kutschireiter A, Surace SC, Sprekeler H, Pfister JP. Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception. Scientific Reports. 7: 8722. PMID 28821729 DOI: 10.1038/s41598-017-06519-y  0.576
2017 Sprekeler H. Functional consequences of inhibitory plasticity: homeostasis, the excitation-inhibition balance and beyond. Current Opinion in Neurobiology. 43: 198-203. PMID 28500933 DOI: 10.1016/j.conb.2017.03.014  0.368
2017 Chenkov N, Sprekeler H, Kempter R. Memory replay in balanced recurrent networks. Plos Computational Biology. 13: e1005359. PMID 28135266 DOI: 10.1371/journal.pcbi.1005359  0.658
2017 Newton AJH, Seidenstein AH, McDougal RA, Pérez-Cervera A, Huguet G, M-Seara T, Haimerl C, Angulo-Garcia D, Torcini A, Cossart R, Malvache A, Skiker K, Maouene M, Ragognetti G, Lorusso L, ... ... Sprekeler H, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0372-1  0.628
2016 Wilmes KA, Sprekeler H, Schreiber S. Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons. Plos Computational Biology. 12: e1004768. PMID 27003565 DOI: 10.1371/journal.pcbi.1004768  0.402
2015 D'Albis T, Jaramillo J, Sprekeler H, Kempter R. Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation. Neural Computation. 27: 1624-72. PMID 26079752 DOI: 10.1162/Neco_A_00752  0.75
2015 Mackwood O, Sprekeler H. Functional requirements for homeostatic inhibitory plasticity in recurrent networks Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P234  0.4
2015 Kutschireiter A, Surace SC, Sprekeler H, Pfister J. Approximate nonlinear filtering with a recurrent neural network Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P196  0.531
2015 Weber SN, Sprekeler H. A model for spatially periodic firing in the hippocampal formation based on interacting excitatory and inhibitory plasticity Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-O6  0.388
2015 D'Albis T, Jaramillo J, Sprekeler H, Kempter R. Inheritance of hippocampal place fields through hebbian learning: Effects of theta modulation and phase precession on structure formation Neural Computation. 27: 1624-1672. DOI: 10.1162/NECO_a_00752  0.753
2014 Sprekeler H, Zito T, Wiskott L. An extension of slow feature analysis for nonlinear blind source separation Journal of Machine Learning Research. 15: 921-947.  0.552
2013 Vogels TP, Froemke RC, Doyon N, Gilson M, Haas JS, Liu R, Maffei A, Miller P, Wierenga CJ, Woodin MA, Zenke F, Sprekeler H. Inhibitory synaptic plasticity: spike timing-dependence and putative network function. Frontiers in Neural Circuits. 7: 119. PMID 23882186 DOI: 10.3389/Fncir.2013.00119  0.781
2013 Frémaux N, Sprekeler H, Gerstner W. Reinforcement learning using a continuous time actor-critic framework with spiking neurons. Plos Computational Biology. 9: e1003024. PMID 23592970 DOI: 10.1371/journal.pcbi.1003024  0.697
2013 Pawlak V, Greenberg DS, Sprekeler H, Gerstner W, Kerr JN. Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo. Elife. 2: e00012. PMID 23359858 DOI: 10.7554/Elife.00012  0.678
2013 Rüter J, Sprekeler H, Gerstner W, Herzog MH. The silent period of evidence integration in fast decision making. Plos One. 8: e46525. PMID 23349660 DOI: 10.1371/journal.pone.0046525  0.647
2013 Chenkov N, Sprekeler H, Kempter R. Phase sequences in balanced recurrent networks Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P207  0.654
2012 Gerstner W, Sprekeler H, Deco G. Theory and simulation in neuroscience. Science (New York, N.Y.). 338: 60-5. PMID 23042882 DOI: 10.1126/Science.1227356  0.632
2012 Rüter J, Marcille N, Sprekeler H, Gerstner W, Herzog MH. Paradoxical evidence integration in rapid decision processes. Plos Computational Biology. 8: e1002382. PMID 22359494 DOI: 10.1371/Journal.Pcbi.1002382  0.707
2012 Herzog MH, Aberg KC, Frémaux N, Gerstner W, Sprekeler H. Perceptual learning, roving and the unsupervised bias. Vision Research. 61: 95-9. PMID 22119774 DOI: 10.1068/V110194  0.673
2012 Pawlak V, Greenberg DS, Sprekeler H, Gerstner W, Kerr JN. Author response: Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo Elife. DOI: 10.7554/Elife.00012.012  0.645
2011 Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W. Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science (New York, N.Y.). 334: 1569-73. PMID 22075724 DOI: 10.1126/Science.1211095  0.762
2011 Sprekeler H. On the relation of slow feature analysis and Laplacian eigenmaps. Neural Computation. 23: 3287-302. PMID 21919780 DOI: 10.1162/NECO_a_00214  0.338
2011 Sprekeler H, Wiskott L. A theory of slow feature analysis for transformation-based input signals with an application to complex cells. Neural Computation. 23: 303-35. PMID 21105830 DOI: 10.1162/NECO_a_00072  0.621
2011 Wiskott L, Berkes P, Franzius M, Sprekeler H, Wilbert N. Slow feature analysis Scholarpedia. 6: 5282. DOI: 10.4249/Scholarpedia.5282  0.735
2011 Zenke F, Hennequin G, Sprekeler H, Vogels TP, Gerstner W. Plasticity and stability in recurrent neural networks Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P120  0.755
2010 Frémaux N, Sprekeler H, Gerstner W. Functional requirements for reward-modulated spike-timing-dependent plasticity. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 30: 13326-37. PMID 20926659 DOI: 10.1523/JNEUROSCI.6249-09.2010  0.687
2009 Schreiber S, Sprekeler H. On the sensitivity of spiking responses to noise Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P255  0.325
2009 Sprekeler H, Hennequin G, Gerstner W. Code-specific policy gradient rules for spiking neurons Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1741-1749.  0.615
2008 Creutzig F, Sprekeler H. Predictive coding and the slowness principle: an information-theoretic approach. Neural Computation. 20: 1026-41. PMID 18085988 DOI: 10.1162/neco.2008.01-07-455  0.307
2007 Franzius M, Sprekeler H, Wiskott L. Slowness and sparseness lead to place, head-direction, and spatial-view cells. Plos Computational Biology. 3: e166. PMID 17784780 DOI: 10.1371/journal.pcbi.0030166  0.638
2007 Sprekeler H, Michaelis C, Wiskott L. Slowness: an objective for spike-timing-dependent plasticity? Plos Computational Biology. 3: e112. PMID 17604445 DOI: 10.1371/journal.pcbi.0030112  0.674
2007 Sprekeler H, Wiskott L. Spike-timing-dependent plasticity and temporal input statistics Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P86  0.681
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