2019

Modeling grid fields instead of modeling grid cells
Sophie Rosay, Simon Weber, Marcello Mulas
Journal of Computational Neuroscience 47(1):43-60
Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types
Loreen Hertaeg, Henning Sprekeler
PLoS Computational Biology 15 (5), e1006999
A local measure of symmetry and orientation for individual spikes of grid cells
Simon Nikolaus Weber, Henning Sprekeler
PLoS Computational Biology 15 (2), e1006804

2018

Sparse bursts optimize information transmission in a multiplexed neural code
R. Naud, H. Sprekeler
PNAS, 115(27):E6329-E6338
Learning place cells, grid cells, and invariances with excitatory and inhibitory plasticity
S.N. Weber, H. Sprekeler
eLife 2018;7:e34560

2017

Memory replay in balanced recurrent networks
N. Chenkov, H. Sprekeler, R. Kempter
PLoS Computational Biology 13(1): e1005359
Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception
A. Kutschireiter, S.C. Surace, H. Sprekeler, J.P. Pfister
Scientific Reports 7:8722, DOI:10.1038/s41598-017-06519-y
Functional consequences of inhibitory plasticity: homeostasis, the excitation-inhibition balance and beyond
H. Sprekeler
Current Opinion in Neurobiology 43, 198-203

2016

Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons
K.A. Wilmes, H. Sprekeler, S. Schreiber
PLoS Computational Biology, 12(2), e1004768

2015

Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession of Structure Formation
T. D'Albis, J. Jaramillo, H. Sprekeler, R. Kempter
Neural Computation, 27(8), 1624-1672

2014

An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
H. Sprekeler, T. Zito and L. Wiskott
Journal of Machine Learning Research 15, 921-947

2013

Reinforcement Learning using a Continuous Time Actor-Critic Framework with Spiking Neurons
N. Fremaux, H. Sprekeler, W. Gerstner
PLoS Computational Biology, 9(4): e1003024
Changing the responses of cortical neurons from sub- to supra-threshold using single spikes in vivo
V. Pawlak, D. S. Greenberg, H. Sprekeler, W. Gerstner, J. Kerr
eLife 2013;2:e00012

2012

The silent period of evidence integration in fast decision making
J. Rüter, H. Sprekeler, W. Gerstner, M. H. Herzog
PloS One 8(1):e46525
Theory and simulation in neuroscience
W. Gerstner, H. Sprekeler, G. Deco
Science 338:60-65
Perceptual learning, Roving & the Unsupervised Bias
M. H. Herzog, K. C. Aberg, N. Fremaux, W. Gerstner, H. Sprekeler
Vision Research, 61:95-99

2011

Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks
T. Vogels*, H. Sprekeler*, F. Zenke, C. Clopath and W. Gerstner
Science, 334:1569-1573
Paradoxical evidence integration in rapid decision processes
J. Rüter, N. Marcille, H. Sprekeler, W. Gerstner and M. Herzog
PLoS Computational Biology, 8(2):e1002382
On the Relation of Slow Feature Analysis and Laplacian Eigenmaps
H. Sprekeler
Neural Computation 23:3287-3302
A Theory of Slow Feature Analysis for Transformation-Based Input Signals with an Application to Complex Cells
H. Sprekeler and L. Wiskott
Neural Computation 23:303-335

2010

Functional Requirements for Reward-modulated Spike Timing-Dependent Plasticity
N. Fremaux*, H. Sprekeler* and W. Gerstner
Journal of Neuroscience 30:13326-13337
Slow Feature Analysis
L. Wiskott, P. Berkes, M. Franzius, H. Sprekeler and N. Wilbert
Scholarpedia, 6(4):5282

2009

Code-Specific Policy-Gradient Rules for Spiking Neurons
H. Sprekeler, G. Hennequin and W.Gerstner
Advances in Neural Information Processing Systems 22 (NIPS 2009)

2008

Predictive Coding and the Slowness Principle: An Information-Theoretic Approach
F. Creutzig and H. Sprekeler
Neural Computation 20:1026-41

2007

Slowness and Sparseness lead to Place, Head-Direction and Spatial-View Cells
M. Franzius*, H. Sprekeler* and L. Wiskott
Neural Computation 20:1026-41
Slowness: An Objective for Spike-Timing-Dependent Plasticity?
H. Sprekeler, C. Michaelis and L. Wiskott
PLoS Computational Biology 3(6):e112

2004

Positive Correlations in Tunneling through coupled Quantum Dots
G. Kießlich, H. Sprekeler, A. Wacker, and E. Schöll
Semiconductor Science and Technology 19, S 37
Coulomb Effects in Tunneling through a Quantum Dot Stack
H. Sprekeler, G. Kießlich, A. Wacker, and E. Schöll
Phys. Rev. B 69, 125328