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Henning Sprekeler
Henning Sprekeler
Technische Universität Berlin
Bestätigte E-Mail-Adresse bei tu-berlin.de
Titel
Zitiert von
Zitiert von
Jahr
Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks
TP Vogels*, H Sprekeler*, F Zenke, C Clopath, W Gerstner
Science 334 (6062), 1569-1573, 2011
7872011
Slowness and sparseness lead to place, head-direction, and spatial-view cells
M Franzius*, H Sprekeler*, L Wiskott
PLoS Computational Biology 3 (8), e166, 2007
2702007
Theory and Simulation in Neuroscience
W Gerstner, H Sprekeler, G Deco
Science 338 (6103), 60-65, 2012
2182012
Reinforcement learning using a continuous time actor-critic framework with spiking neurons
N Frémaux, H Sprekeler, W Gerstner
PLoS computational biology 9 (4), e1003024, 2013
2132013
Functional requirements for reward-modulated spike-timing-dependent plasticity
N Frémaux*, H Sprekeler*, W Gerstner
The Journal of Neuroscience 30 (40), 13326-13337, 2010
1752010
Inhibitory synaptic plasticity: spike timing-dependence and putative network function
TP Vogels, RC Froemke, N Doyon, M Gilson, JS Haas, R Liu, A Maffei, ...
Frontiers in neural circuits 7, 119, 2013
1652013
Sparse bursts optimize information transmission in a multiplexed neural code
R Naud, H Sprekeler
Proceedings of the National Academy of Sciences, 201720995, 2018
1292018
Slowness: An objective for spike timing-dependent plasticity?
H Sprekeler, C Michaelis, L Wiskott
PLoS Computational Biology 3 (6), e112, 2007
1022007
On the relation of slow feature analysis and laplacian eigenmaps
H Sprekeler
Neural computation 23, 303-335, 2011
912011
An extension of slow feature analysis for nonlinear blind source separation
H Sprekeler, T Zito, L Wiskott
The Journal of Machine Learning Research 15 (1), 921-947, 2014
88*2014
Functional consequences of inhibitory plasticity: homeostasis, the excitation-inhibition balance and beyond
H Sprekeler
Current opinion in neurobiology 43, 198-203, 2017
872017
Predictive coding and the slowness principle: An information-theoretic approach
F Creutzig, H Sprekeler
Neural Computation 20 (4), 1026-1041, 2008
762008
A thalamocortical top-down circuit for associative memory
MB Pardi, J Vogenstahl, T Dalmay, T Spanò, DL Pu, LB Naumann, ...
Science 370 (6518), 844-848, 2020
702020
Memory replay in balanced recurrent networks
N Chenkov, H Sprekeler, R Kempter
PLoS computational biology 13 (1), e1005359, 2017
682017
Slow feature analysis
L Wiskott
Encyclopedia of Computational Neuroscience, 3142-3143, 2022
592022
Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception
A Kutschireiter, SC Surace, H Sprekeler, JP Pfister
Scientific reports 7 (1), 8722, 2017
582017
Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity
SN Weber, H Sprekeler
Elife 7, e34560, 2018
532018
Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types
L Hertäg, H Sprekeler
PLoS computational biology 15 (5), e1006999, 2019
522019
Inhibition as a binary switch for excitatory plasticity in pyramidal neurons
KA Wilmes, H Sprekeler, S Schreiber
PLoS computational biology 12 (3), e1004768, 2016
522016
Learning prediction error neurons in a canonical interneuron circuit
L Hertäg, H Sprekeler
eLife 9, e57541, 2020
482020
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