• R. Naud, H. Sprekeler (2018)
  Sparse bursts optimize information transmission in a multiplexed neural code
  PNAS, 115(27):E6329-E6338
  pdf

• S.N. Weber, H. Sprekeler (2018)
  Learning place cells, grid cells, and invariances with excitatory and inhibitory plasticity
  eLife 7, e34560
  pdf

• A. Kutschireiter, S.C.  Surace, H.  Sprekeler, J.P.  Pfister (2017)
  Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception
  Scientific Reports 7:8722, DOI:10.1038/s41598-017-06519-y
  pdf

• H. Sprekeler (2017)
  Functional consequences of inhibitory plasticity: homeostasis, the excitation-inhibition balance and beyond
  Current Opinion in Neurobiology 43, 198-203
  pdf

• N. Chenkov, H. Sprekeler, R. Kempter (2017)
  Memory replay in balanced recurrent networks
  PLoS Computational Biology 13(1): e1005359
  pdf

• K.A. Wilmes, H. Sprekeler, S. Schreiber (2016)
  Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons
  PLoS Computational Biology, 12(2), e1004768
  pdf

• T. D'Albis, J. Jaramillo, H. Sprekeler, R. Kempter (2015)
  Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession of Structure Formation
  Neural Computation, 27(8), 1624-1672
  pdf

• H. Sprekeler, T. Zito and L. Wiskott (2014)
  An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
  Journal of Machine Learning Research 15, 921-947
  pdf

• N. Fremaux, H. Sprekeler, W. Gerstner (2013)
  Reinforcement Learning using a Continuous Time Actor-Critic Framework with Spiking Neurons
  PLoS Computational Biology, 9(4): e1003024
  pdf
  

• V. Pawlak, D. S. Greenberg, H. Sprekeler, W. Gerstner, J. Kerr (2013)
  Changing the responses of cortical neurons from sub- to supra-threshold using single spikes in vivo
  eLife 2013;2:e00012
  pdf
  

• J. Rüter, H. Sprekeler, W. Gerstner, M. H. Herzog (2012)
  The silent period of evidence integration in fast decision making
  PloS One 8(1):e46525
  pdf
  

• W. Gerstner, H. Sprekeler, G. Deco (2012)
  Theory and simulation in neuroscience
  Science 338:60-65
  pdf on the Science website
  

• M. H. Herzog, K. C. Aberg, N. Fremaux, W. Gerstner, H. Sprekeler (2012)
  Perceptual learning, Roving & the Unsupervised Bias
  Vision Research, 61:95-99
  pdf available online
  

• T. Vogels*, H. Sprekeler*, F. Zenke, C. Clopath and W. Gerstner (2011)
  Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks
  Science, 334:1569-1573
  look here for a pdf

• J. Rüter, N. Marcille, H. Sprekeler, W. Gerstner and M. Herzog (2011)
  Paradoxical evidence integration in rapid decision processes
  PLoS Computational Biology, 8(2):e1002382
  pdf
  

• H. Sprekeler (2011)
  On the Relation of Slow Feature Analysis and Laplacian Eigenmaps
  Neural Computation 23:3287-3302
  pdf

• H. Sprekeler and L. Wiskott (2011)
  A Theory of Slow Feature Analysis for Transformation-Based Input Signals
  with an Application to Complex Cells
  Neural Computation 23:303-335
  pdf

• N. Fremaux*, H. Sprekeler* and W. Gerstner (2010)
  Functional Requirements for Reward-modulated Spike Timing-Dependent Plasticity
  Journal of Neuroscience 30:13326-13337
  pdf
  

• L. Wiskott, P. Berkes, M. Franzius, H. Sprekeler and N. Wilbert (2010)
  Slow Feature Analysis
  Scholarpedia, 6(4):5282
  link

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

• F. Creutzig and H. Sprekeler (2008)
  Predictive Coding and the Slowness Principle: An Information-Theoretic Approach
  Neural Computation 20:1026-41
  pdf

• M. Franzius*, H. Sprekeler* and L. Wiskott (2007)
  Slowness and Sparseness lead to Place, Head-Direction and Spatial-View Cells
  PLoS Computational Biology, 3(8):e166
  pdf

• H. Sprekeler, C. Michaelis and L. Wiskott (2007)
  Slowness: An Objective for Spike-Timing-Dependent Plasticity?
  PLoS Computational Biology 3(6):e112
  pdf

• G. Kießlich, H. Sprekeler, A. Wacker, and E. Schöll (2004)
  Positive Correlations in Tunneling through coupled Quantum Dots
  Semiconductor Science and Technology 19, S 37
  (pdf on cond-mat)

• H. Sprekeler, G. Kießlich, A. Wacker, and E. Schöll (2004)
  Coulomb Effects in Tunneling through a Quantum Dot Stack
  Phys. Rev. B 69, 125328
  (pdf on cond-mat)

</ul>

• S.N. Weber, H. Sprekeler (2018)
  A local measure of symmetry and orientation for individual spikes of grid cells
  bioRxiv, doi.org/10.1101/425637
  pdf, website
• L. Hertäg, H. Sprekeler (2018)
  Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types
  bioRxiv, DOI:https://doi.org/10.1101/410340
  pdf
• R. Naud, H. Sprekeler
  Burst Ensemble Multiplexing: A Neural Code Connecting Dendritic Spikes with Microcircuits 
  bioRxiv, doi.org/10.1101/143636
  pdf
• S.N. Weber, H. Sprekeler
  Learning place cells, grid cells and invariances: A unifying model 
  bioRxiv, doi.org/10.1101/102525
  pdf
• C. Clopath, T.P. Vogels, R.C. Froemke, H. Sprekeler
  Receptive field formation by interacting excitatory and inhibitory synaptic plasticity 
  bioRxiv, doi.org/10.1101/066589
  pdf