Henning Sprekeler

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Wulfram GerstnerEPFLE-mail confirmado em epfl.ch
Laurenz WiskottProfessor of Theory of Neural Systems, Institut für Neuroinformatik, Ruhr-Universität BochumE-mail confirmado em ini.rub.de
Tim P. VogelsInstitute of Science and Technology, AustriaE-mail confirmado em ist.ac.at
Friedemann ZenkeFriedrich Miescher Institute (FMI), University of BaselE-mail confirmado em fmi.ch
Prof. Claudia ClopathBioengineering, Imperial College LondonE-mail confirmado em imperial.ac.uk
Nicolas FrémauxPhD student, Brain Mind Institiute, Ecole Polytechnique de LausanneE-mail confirmado em epfl.ch
Joram KeijserUniversity College LondonE-mail confirmado em ucl.ac.uk
Laura Bella NaumannInstitute of Science and Technology, AustriaE-mail confirmado em ist.ac.at
Robert Tjarko LangeSakana AI, TU BerlinE-mail confirmado em tu-berlin.de
Loreen HertägTU BerlinE-mail confirmado em tu-berlin.de
Richard NaudDepartment of Cellular and Molecular Medicine, Department of Physics, University of OttawaE-mail confirmado em uottawa.ca
Robert FroemkeNYU School of MedicineE-mail confirmado em med.nyu.edu
M. Belén PardiInserm, Institute of Psychiatry and Neuroscience of ParisE-mail confirmado em inserm.fr
Tamas DalmayProfessor of RNA Biology, University of East AngliaE-mail confirmado em uea.ac.uk
Richard KempterInstitute for Theoretical BiologyE-mail confirmado em biologie.hu-berlin.de
Michael HerzogEPFL, SwitzerlandE-mail confirmado em epfl.ch
Mathias FranziusHonda Research Institute EuropeE-mail confirmado em honda-ri.de
Simon N WeberTechnische Universität BerlinE-mail confirmado em tu-berlin.de
Jean-Pascal PfisterProfessor of Theoretical Neuroscience, Department of Physiology, University of BernE-mail confirmado em unibe.ch
Simone Carlo SuracePostdoctoral fellow, Department of Physiology, University of Bern and Institute for NeuroinformaticsE-mail confirmado em unibe.ch

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Henning Sprekeler

Technische Universität Berlin

E-mail confirmado em tu-berlin.de

Computational Neuroscience


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	809	2011
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	270	2007
Theory and Simulation in Neuroscience W Gerstner, H Sprekeler, G Deco Science 338 (6103), 60-65, 2012	222	2012
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	215	2013
Functional requirements for reward-modulated spike-timing-dependent plasticity N Frémaux, H Sprekeler, W Gerstner The Journal of Neuroscience 30 (40), 13326-13337, 2010	181	2010
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	168	2013
Sparse bursts optimize information transmission in a multiplexed neural code R Naud, H Sprekeler Proceedings of the National Academy of Sciences, 201720995, 2018	134	2018
Slowness: An objective for spike timing-dependent plasticity? H Sprekeler, C Michaelis, L Wiskott PLoS Computational Biology 3 (6), e112, 2007	102	2007
On the relation of slow feature analysis and laplacian eigenmaps H Sprekeler Neural computation 23, 303-335, 2011	91	2011
Functional consequences of inhibitory plasticity: homeostasis, the excitation-inhibition balance and beyond H Sprekeler Current opinion in neurobiology 43, 198-203, 2017	89	2017
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	89*	2014
Predictive coding and the slowness principle: An information-theoretic approach F Creutzig, H Sprekeler Neural Computation 20 (4), 1026-1041, 2008	77	2008
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	75	2020
Memory replay in balanced recurrent networks N Chenkov, H Sprekeler, R Kempter PLoS computational biology 13 (1), e1005359, 2017	70	2017
Slow feature analysis L Wiskott Encyclopedia of Computational Neuroscience, 3142-3143, 2022	59	2022
Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception A Kutschireiter, SC Surace, H Sprekeler, JP Pfister Scientific reports 7 (1), 8722, 2017	59	2017
Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity SN Weber, H Sprekeler Elife 7, e34560, 2018	58	2018
Inhibition as a binary switch for excitatory plasticity in pyramidal neurons KA Wilmes, H Sprekeler, S Schreiber PLoS computational biology 12 (3), e1004768, 2016	53	2016
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	52	2019
Learning prediction error neurons in a canonical interneuron circuit L Hertäg, H Sprekeler eLife 9, e57541, 2020	51	2020

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