Henning Sprekeler
Affiliations: | University of Cambridge, Cambridge, England, United Kingdom |
Area:
Computational NeuroscienceWebsite:
http://learning.eng.cam.ac.uk/Public/Sprekeler/WebHomeGoogle:
"Henning Sprekeler"Mean distance: 13.43 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| Laurenz Wiskott | grad student | 2004-2008 | HU Berlin |
| Richard Kempter | post-doc | 2011- | HU Berlin |
| Wulfram Gerstner | post-doc | 2008-2011 | EPFL |
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Publications
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| Remme MWH, Bergmann U, Alevi D, et al. (2021) Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation. Plos Computational Biology. 17: e1009681 |
| Vercruysse F, Naud R, Sprekeler H. (2021) Self-organization of a doubly asynchronous irregular network state for spikes and bursts. Plos Computational Biology. 17: e1009478 |
| Mackwood O, Naumann LB, Sprekeler H. (2021) Learning excitatory-inhibitory neuronal assemblies in recurrent networks. Elife. 10 |
| Hertäg L, Sprekeler H. (2020) Learning prediction error neurons in a canonical interneuron circuit. Elife. 9 |
| Naumann LB, Sprekeler H. (2020) Presynaptic inhibition rapidly stabilises recurrent excitation in the face of plasticity. Plos Computational Biology. 16: e1008118 |
| Hertäg L, Sprekeler H. (2020) Author response: Learning prediction error neurons in a canonical interneuron circuit Elife |
| Hertäg L, Sprekeler H. (2019) Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types. Plos Computational Biology. 15: e1006999 |
| Naud R, Sprekeler H. (2018) Sparse bursts optimize information transmission in a multiplexed neural code. Proceedings of the National Academy of Sciences of the United States of America |
| Weber SN, Sprekeler H. (2018) Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity. Elife. 7 |
| Weber SN, Sprekeler H. (2018) Author response: Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity Elife |