2016


L. A. Gatys, A. S. Ecker, M. Bethge, A. Hertzmann, and E. Shechtman
Controlling Perceptual Factors in Neural Style Transfer
arXiv, 2016
#texture transfer, #artistic style, #user control, #convolutional neural networks
URL, Supplementary Material, BibTex
R. Hosseini, S. Sra, L. Theis, and M. Bethge
Inference and Mixture Modeling with the Elliptical Gamma Distribution
Computational Statistics and Data Analysis, 101, 29-43, 2016
URL, DOI, BibTex
L. A. Gatys, M. Bethge, A. Hertzmann, and E. Shechtman
Preserving Color in Neural Artistic Style Transfer
arXiv, 2016
#texture transfer, #artistic style, #color preservation, #convolutional neural networks
URL, BibTex
L. A. Gatys, A. S. Ecker, and M. Bethge
Image Style Transfer Using Convolutional Neural Networks
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016
#texture transfer, #artistic style, #separating content from style, #convolutional neural networks
URL, BibTex
I. Ustyuzhaninov, W. Brendel, L. A. Gatys, and M. Bethge
Texture Synthesis Using Shallow Convolutional Networks with Random Filters
arXiv, 2016
#texture synthesis, #random filters, #convolutional neural networks, #deep learning
URL, PDF, BibTex
L. Theis, P. Berens, E. Froudarakis, J. Reimer, M. Roman-Roson, T. Baden, T. Euler, A. S. Tolias, et al.
Benchmarking spike rate inference in population calcium imaging
Neuron, 90(3), 471-482, 2016
#two-photon imaging, #spiking neurons
Code, URL, DOI, BibTex
D. Kobak, W. Brendel, C. Constantinidis, C. E. Feierstein, A. Kepecs, Z. F. Mainen, R. Romo, X.-L. Qi, et al.
Demixed principal component analysis of neural population data
eLife, 5, 2016
URL, DOI, BibTex
T. S. A. Wallis, M. Bethge, and F. A. Wichmann
Testing models of peripheral encoding using metamerism in an oddity paradigm
Journal of Vision, 16(2), 2016
Code, URL, DOI, BibTex
A. S. Ecker, G. H. Denfield, M. Bethge, and A. S. Tolias
On the Structure of Neuronal Population Activity under Fluctuations in Attentional State
Journal of Neuroscience, 36(5), 1775-1789, 2016
#attention, #gain modulation, #noise correlations, #population coding
Code, URL, DOI, PDF, BibTex
C. R. Cadwell, A. Palasantza, X. Jiang, P. Berens, Q. Deng, J. Reimer, K. Tolias, M. Bethge, et al.
Morphological, electrophysiological and transcriptomic profiling of single neurons using Patch-seq
Nature Biotechnology, 34, 199-203, 2016
URL, BibTex
T. Baden, P. Berens, K. Franke, M. Rezac, M. Bethge, and T. Euler
The functional diversity of retinal ganglion cells in the mouse
Nature, 529, 345-350, 2016
#retina, #clustering, #machine learning, #cell types, #ganglion cells
Code, URL, DOI, Dataset, BibTex
A. Mathis, D. Rokni, V. Kapoor, M. Bethge, and V. N. Murthy
Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing
Neuron, 2016
URL, BibTex
L. Theis, A. van den Oord, and M. Bethge
A note on the evaluation of generative models
International Conference on Learning Representations (arXiv:1511.01844), 2016
URL, PDF, BibTex

2015


X. Jiang, S. Shen, C. Cadwell, P. Berens, F. Sinz, A. S. Ecker, S. Patel, and A. Tolias
Principles of connectivity among morphologically defined cell types in adult neocortex
Science, 350(6264), 1055, 2015
#connectivity, #interneurons, #morphology, #machine learning
URL, PDF, BibTex
M. Kuemmerer, T. Wallis, and M. Bethge
Information-theoretic model comparison unifies saliency metrics
Proceedings of the National Academy of Science, 112(52), 16054-16059, 2015
URL, DOI, BibTex
L. A. Gatys, A. S. Ecker, and M. Bethge
A Neural Algorithm of Artistic Style
arXiv, 2015
#artistic style, #convolutional neural networks, #separating content from style
URL, Details, BibTex
L. Theis and M. Bethge
Generative Image Modeling Using Spatial LSTMs
Advances in Neural Information Processing Systems 28, 2015
#deep learning, #generative modeling, #natural image statistics, #lstm, #mcgsm
Code, URL, PDF, Supplemental, BibTex
L. A. Gatys, A. S. Ecker, T. Tchumatchenko, and M. Bethge
Synaptic unreliability facilitates information transmission in balanced cortical populations
Physical Review E, 91(6), 62707, 2015
#synaptic noise, #balanced state, #neural population coding
Code, URL, DOI, PDF, BibTex
L. A. Gatys, A. S. Ecker, and M. Bethge
Texture Synthesis Using Convolutional Neural Networks
Advances in Neural Information Processing Systems 28, 2015
#texture synthesis, #ventral stream, #convolutional neural networks, #deep learning
Code, URL, PDF, Example textures, BibTex
M. Kümmerer, L. Theis, and M. Bethge
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
ICLR Workshop, 2015
#saliency, #deep learning
URL, PDF, BibTex
S. Sra, R. Hosseini, L. Theis, and M. Bethge
Data modeling with the elliptical gamma distribution
Artificial Intelligence and Statistics, 2015
#density estimation, #natural image statistics
URL, BibTex
H. E. Gerhard, L. Theis, and M. Bethge
Modeling Natural Image Statistics
Biologically-inspired Computer Vision—Fundamentals and Applications (to appear), Wiley VCH, 2015, ISBN 978-3527412648
#natural image statistics, #mcgsm, #ica, #psychophysics
URL, ISBN, PDF, BibTex

2014


F. Sinz, J.-P. Lies, S. Gerwinn, and M. Bethge
Natter: A Python Natural Image Statistics Toolbox
Journal of Statistical Software, 61(5), 2014
#natural image statistics, #software, #python
Code, PDF, BibTex
M. Kümmerer, T. Wallis, and M. Bethge
How close are we to understanding image-based saliency?
arXiv, 2014
#saliency
URL, BibTex
H. E. Gerhard and M. Bethge
Towards rigorous study of artistic style: a new psychophysical paradigm
Art and Perception, 2, 23-44, 2014
#psychophysics, #texture discrimination, #stylometry
Code, URL, DOI, PDF, BibTex
A. S. Ecker and A. S. Tolias
Is there signal in the noise?
Nature Neuroscience, 17, 750-751, 2014
#variability, #modulated poisson, #noise correlations
URL, DOI, BibTex
E. Froudarakis, P. Berens, A. S. Ecker, R. J. Cotton, F. H. Sinz, D. Yatsenko, P. Saggau, M. Bethge, et al.
Population code in mouse V1 facilitates read-out of natural scenes through increased sparseness
Nature Neuroscience, 17, 851-857, 2014
#sparsity, #natural image statistics, #population coding, #v1, #two-photon imaging
URL, DOI, PDF, BibTex
M. Bethge
Efficient Population Coding
Encyclopedia of Computational Neuroscience, Springer New York, 2014
#population coding
URL, DOI, PDF, BibTex
A. S. Ecker, P. Berens, R. J. Cotton, M. Subramaniyan, G. H. Denfield, C. R. Cadwell, S. M. Smirnakis, M. Bethge, et al.
State dependence of noise correlations in macaque primary visual cortex
Neuron, 82(1), 235-248, 2014
#noise correlations, #gpfa, #population, #anesthesia, #macaque
Code, URL, DOI, PDF, BibTex
J.-P. Lies, R. M. Häfner, and M. Bethge
Slowness and sparseness have diverging effects on complex cell learning
PLoS Computational Biology, 10(3), 2014
#slowness, #sparsity, #complex cell, #natural image statistics, #unsupervised learning
Code, URL, DOI, PDF, BibTex

2013


A. M. Chagas, L. Theis, B. Sengupta, M. Stüttgen, M. Bethge, and C. Schwarz
Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents
Frontiers in Neural Circuits, 7(190), 2013
URL, PDF, BibTex
L. Theis, A. M. Chagas, D. Arnstein, C. Schwarz, and M. Bethge
Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification
PLoS Computational Biology, 9(11), 2013
#generalized linear model, #spiking neurons, #mixture models
Code, URL, DOI, PDF, BibTex
F. Sinz and M. Bethge
What is the Limit of Redundancy Reduction with Divisive Normalization?
Neural Computation, 2013
URL, PDF, BibTex
T. Baden, L. P. Godino, S. Yusuf, and P. Berens
Neurowissenschaften in Afrika - Kooperationen und Perspektiven
Neuroforum, 19(2), 73-74, 2013
PDF, BibTex
M. Subramaniyan, A. S. Ecker, P. Berens, and A. S. Tolias
Macaque monkeys perceive the flash lag illusion
PLoS ONE (e58788), 8(3), 2013
#macaque, #flash-lag, #psychophysics, #illusion
Code, URL, BibTex
R. M. Haefner, S. Gerwinn, J. H. Macke, and M. Bethge
Inferring decoding strategies from choice probabilities in the presence of correlated variability
Nature Neuroscience, 16, 235-242, 2013
#noise correlations, #choice probabilities, #decision making, #population coding
Code, URL, PDF, Perspective, BibTex
F. Sinz and M. Bethge
Temporal adaptation enhances efficient contrast gain control on natural images
PLoS Computational Biology, 9(1), 2013
#natural image statistics, #divisive normalization, #contrast gain control, #lp-spherically symmetric distributions
Code, URL, PDF, BibTex
T. Baden, P. Berens, M. Bethge, and T. Euler
Spikes in Mammalian Bipolar Cells Support Temporal Layering of the Inner Retina
Current Biology, 23(1), 48-52, 2013
#retina, #bipolar cells, #population coding
URL, DOI, PDF, BibTex
H. E. Gerhard, F. A. Wichmann, and M. Bethge
How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?
PLoS Computational Biology, 9(1), 2013
#natural image statistics, #psychophysics
URL, PDF, BibTex

2012


L. Theis, J. Sohl-Dickstein, and M. Bethge
Training sparse natural image models with a fast Gibbs sampler of an extended state space
Advances in Neural Information Processing Systems 25, 2012
#natural image statistics, #ica, #overcompleteness
Code, PDF, Supplemental, Poster, BibTex
P. Berens, A. S. Ecker, R. J. Cotton, W. J. Ma, M. Bethge, and A. S. Tolias
A fast and simple population code for orientation in primate V1
Journal of Neuroscience, 32(31), 10618-10626, 2012
#population coding, #orientation, #v1, #macaque, #logistic regression, #multi-tetrode recordings, #noise correlations
Code, URL, PDF, Dataset, BibTex
L. Theis, R. Hosseini, and M. Bethge
Mixtures of Conditional Gaussian Scale Mixtures Applied to Multiscale Image Representations
PLoS ONE, 7(7), 2012
#natural image statistics, #gaussian scale mixtures, #random fields, #mcgsm
Code, DOI, PDF, BibTex
T. Putzeys, M. Bethge, F. A. Wichmann, J. Wagemans, and R. Goris
A New Perceptual Bias Reveals Suboptimal Population Decoding of Sensory Responses
PLoS Computational Biolology, 8(4), 2012
URL, DOI, PDF, BibTex
P. Berens, N. K. Logothetis, and A. S. Tolias
Local field potentials, BOLD and spiking activity: Relationships and physiological mechanisms
Visual population codes – towards a common multivariate framework for cell recording and functional imaging, MIT Press, 2012
#lfp, #bold, #gamma
URL, PDF, BibTex

2011


L. Theis, S. Gerwinn, F. Sinz, and M. Bethge
In All Likelihood, Deep Belief Is Not Enough
Journal of Machine Learning Research, 12, 3071-3096, 2011
#natural image statistics, #deep belief networks, #boltzmann machines, #deep learning
Code, PDF, BibTex
A. S. Ecker, P. Berens, A. S. Tolias, and M. Bethge
The effect of noise correlations in populations of diversely tuned neurons
The Journal of Neuroscience, 31(40), 14272-14283, 2011
#noise correlations, #population coding, #fisher information, #orientation
Code, URL, DOI, PDF, BibTex
J. H. Macke, M. Opper, and M. Bethge
Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity
Physical Review Letters, 106(20), 2011
#population coding
DOI, PDF, BibTex
P. Berens, A. S. Ecker, S. Gerwinn, A. S. Tolias, and M. Bethge
Reassessing optimal neural population codes with neurometric functions
Proceedings of the National Academy of Sciences of the United States of America, 108(11), 4423-4428, 2011
#fisher information, #population coding, #mean squared error, #discrimination error, #neurometric function
Code, URL, PDF, BibTex
J. Macke, P. Berens, and M. Bethge
Statistical analysis of multi-cell recordings: linking population coding models to experimental data
Frontiers in Computational Neuroscience, 5(35), 2011
#multi-cell recordings, #population models, #statistical analysis
URL, PDF, BibTex
T. Kitching, A. Amara, M. Gill, S. Harmeling, C. Heymans, R. Massey, B. Rowe, T. Schrabback, et al.
Gravitational Lensing Accuracy Testing 2010 (GREAT10) Challenge Handbook
The Annals of Applied Statistics, 5(3), 2231-2263, 2011
URL, BibTex
S. Gerwinn, J. Macke, and M. Bethge
Reconstructing stimuli from the spike times of leaky integrate and fire neurons
Frontiers in Neuroscience, 5, 2011
#population coding, #decoding, #bayesian inference, #spiking neurons
URL, DOI, PDF, BibTex

2010


F. Sinz and M. Bethge
Lp-nested symmetric distributions
Journal of Machine Learning Research, 11, 3409-3451, 2010
#natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions
PDF, BibTex
R. Hosseini, F. Sinz, and M. Bethge
Lower bounds on the redundancy of natural images
Vision Research, 50(22), 2213-2222, 2010
#natural image statistics
PDF, BibTex
A. S. Ecker, P. Berens, G. A. Keliris, M. Bethge, N. K. Logothetis, and A. S. Tolias
Decorrelated Neuronal Firing in Cortical Microcircuits
Science, 327(5965), 584-587, 2010
#noise correlations, #multi-tetrode recordings, #v1, #macaque
Code, URL, DOI, PDF, Dataset, BibTex
R. Häfner and M. Bethge
Evaluating neuronal codes for inference using Fisher information
Advances in Neural Information Processing Systems 23, 2010
#population coding, #fisher information
PDF, BibTex
S. Bridle, S. T. Balan, M. Bethge, M. Gentile, S. Harmeling, C. Heymans, M. Hirsch, R. Hosseini, et al.
Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing
Monthly Notices of the Royal Astronomical Society, 2010
BibTex
S. Gerwinn, J. Macke, and M. Bethge
Bayesian inference for generalized linear models for spiking neurons
Frontiers in Computational Neuroscience, 4, 2010
#bayesian inference, #generalized linear model, #spiking neurons
Code, URL, DOI, PDF, BibTex
J. H. Macke, S. Gerwinn, L. White, M. Kaschube, and M. Bethge
Gaussian process methods for estimating cortical maps
NeuroImage, 56(2), 570-581, 2010
#gaussian process
Code, URL, DOI, PDF, BibTex
J. H. Macke and F. A. Wichmann
Estimating predictive stimulus features from psychophysical data: The decision image technique applied to human faces
Journal of Vision, 10(5), 2010
URL, DOI, BibTex

2009


R. Hosseini and M. Bethge
Spectral Stacking: Unbiased Shear Estimation for Weak Gravitational Lensing
Max Planck Institute for Biological Cybernetics, 2009
PDF, BibTex
S. Gerwinn, J. Macke, and M. Bethge
Bayesian population decoding of spiking neurons
Frontiers in Computational Neuroscience, 3, 2009
#population coding, #decoding
URL, DOI, PDF, BibTex
F. H. Sinz, S. Gerwinn, and M. Bethge
Characterization of the p-Generalized Normal Distribution
Journal of Multivariate Analysis, 100(5), 817-820, 2009
#p-generalized normal distribution, #uniqueness theorem, #power exponential distribution
URL, DOI, PDF, BibTex
J. Eichhorn, F. Sinz, and M. Bethge
Natural Image Coding in V1: How Much Use Is Orientation Selectivity?
PLoS Computational Biology, 5(4), 2009
#natural image models, #natural image statistics, #normative models
Code, DOI, PDF, BibTex
J. Macke, M. Opper, and M. Bethge
The effect of pairwise neural correlations on global population statistics
Max Planck Institute for Biological Cybernetics, 2009
PDF, BibTex
J. Macke, P. Berens, A. Ecker, A. Tolias, and M. Bethge
Generating Spike Trains with Specified Correlation-Coeffcients
Neural Computation, 2009
#spike train, #correlated poisson, #multivariate poisson, #noise correlations, #discretized gaussian
Code, PDF, BibTex
F. H. Sinz, E. Simoncelli, and M. Bethge
Hierarchical Modeling of Local Image Features through Lp-Nested Symmetric Distributions
Advances in Neural Information Processing Systems 22, 2009
#natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions
Code, PDF, BibTex
J. H. Macke, S. Gerwinn, M. Kaschube, L. E. White, and M. Bethge
Bayesian estimation of orientation preference maps
Advances in Neural Information Processing Systems 22, 2009
#bayesian inference, #orientation maps
Code, PDF, BibTex
S. Gerwinn, P. Berens, and M. Bethge
A joint maximum-entropy model for binary neural population patterns and continuous signals
Advances in Neural Information Processing Systems 22, 2009
#maximum entropy, #population coding
Code, PDF, BibTex
P. Berens, S. Gerwinn, A. S. Ecker, and M. Bethge
Neurometric function analysis of population codes
Advances in Neural Information Processing Systems 22, 2009
#population coding, #neurometric function
Code, PDF, BibTex
P. Berens
CircStat: A Matlab Toolbox for Circular Statistics
Journal of Statistical Software, 2009
#circular statistics, #directional statistics, #software, #matlab
Code, URL, PDF, BibTex

2008


P. Berens, G. A. Keliris, A. S. Ecker, N. K. Logothetis, and A. S. Tolias
Comparing the feature selectivity of the gamma-band of the local field potential and the underlying spiking activity in primate visual cortex
Frontiers in Systems Neuroscience, 2008
#local field potential, #lfp, #orientation tuning, #ocular dominance, #gamma
URL, DOI, PDF, BibTex
P. Berens, G. A. Keliris, A. S. Ecker, N. K. Logothetis, and A. S. Tolias
Feature selectivity of the gamma-band of the local field potential in primate primary visual cortex
Frontiers in Neuroscience, 2008
URL, DOI, PDF, BibTex
M. Bethge and P. Berens
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
Advances in Neural Information Processing Systems 20, 2008
#population coding, #natural image statistics, #maximum entropy
Code, PDF, BibTex
F. Sinz and M. Bethge
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
Advances in Neural Information Processing Systems 21, 2008
#contrast gain control, #normative models, #natural image statistics, #lp-spherically symmetric distributions
Code, PDF, BibTex
J. H. Macke, G. Zeck, and M. Bethge
Receptive Fields without Spike-Triggering
Advances in Neural Information Processing Systems 20, 2008
#receptive fields, #retina, #population coding
PDF, BibTex
F. H. Sinz, O. Chapelle, A. Agarwal, and B. Schölkopf
An Analysis of Inference with the Universum
Advances in Neural Information Processing Systems 20, 2008
PDF, BibTex
S. Gerwinn, J. Macke, M. Seeger, and M. Bethge
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Advances in Neural Information Processing Systems 20, 2008
PDF, BibTex
F. H. Sinz and M. Bethge
How much can orientation selectivity and contrast gain control reduce the redundancies in natural images
Max Planck Institute for Biological Cybernetics, 2008
#natural image models, #natural image statistics, #normative models, #ica, #contrast gain control
PDF, BibTex
M. Bethge
Der kollektiven Signalverarbeitung von Nervenzellen auf der Spur
Max-Planck Jahrbuch, 2008
BibTex

2007


M. Seeger, S. Gerwinn, and M. Bethge
Bayesian Inference for Sparse Generalized Linear Models
Lecture Notes in Computer Science, 2007
BibTex
M. Bethge and C. Kayser
Do We Know What the Early Visual System Computes?
Proceedings of the 31st Göttingen Neurobiology Conference, 2007
BibTex
M. Bethge, S. Gerwinn, and J. H. Macke
Unsupervised learning of a steerable basis for invariant image representations
Proceedings of SPIE Human Vision and Electronic Imaging XII (EI105), 2007
PDF, BibTex
M. Bethge, T. V. Wiecki, and F. A. Wichmann
The Independent Components of Natural Images are Perceptually Dependent
Proceedings of SPIE Human Vision and Electronic Imaging XII (EI105), 2007
#natural image statistics, #ica, #psychophysics, #perception
PDF, BibTex

2006


M. Bethge
Factorial coding of natural images: How effective are linear model in removing higher-order dependencies?
Journal of the Optical Society of America A, 2006
BibTex
F. H. Sinz and B. Schölkopf
Minimal Logical Constraint Covering Sets
Max Planck Institute for Biological Cybernetics, 2006
#linear programming, #logical constraints, #covering set
PDF, BibTex
J. Weston, R. Collobert, F. Sinz, L. Bottou, and V. Vapnik
Inference with the Universum
Proceedings of the 23rd international conference on Machine learning ICML 06, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, BibTex
J. Quinonero-Candela, C. E. Rasmussen, F. Sinz, and B. Schoelkopf
Evaluating Predictive Uncertainty Challenge
Machine Learning Challenges, Springer, 2006
#machine learning challenge, #predictive uncertainty
URL, BibTex
R. Collobert, F. Sinz, J. Weston, and L. Bottou
Trading Convexity for Scalability
Proceedings of the 23rd international conference on Machine learning ICML 06, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, BibTex
R. Collobert, F. Sinz, J. Weston, and L. Bottou
Large scale transductive SVMs
Journal of Machine Learning Research, 7, 1687-1712, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, BibTex

2004


G. Silberberg, M. Bethge, H. Markram, K. Pawelzik, and M. Tsodyks
Dynamics of population rate codes in ensembles of neocortical neurons
Journal of Neurophysiology, 2004
BibTex
F. Sinz, G. Quinonero-Candela, G. Bakir, C. Rassmussen, and M. Franz
Learning Depth From Stereo
Pattern Recognition Proc 26th DAGM Symposium LNCS 3175, 2004
#camera calibration, #machine learning
PDF, BibTex
D. Goeruer, C. E. Rasmussen, A. S. Tolias, F. Sinz, and N. K. Logothetis
Modelling Spikes with Mixtures of Factor Analysers
Pattern Recognition Proc 26th DAGM Symposium LNCS 3175, 2004
#spike sorting, #clustering, #mixture of factor analyzers
URL, PDF, BibTex

2003


M. Bethge, D. Rotermund, and K. Pawelzik
Optimal neural rate coding leads to bimodal firing rate distributions
Network: Computation in Neural Systems, 2003
#population coding
PDF, BibTex

2002


M. Bethge, D. Rotermund, and K. Pawelzik
Optimal short-term population coding: when Fisher information fails
Neural Computation, 2002
#population coding, #fisher information
URL, DOI, PDF, BibTex
M. Bethge, D. Rotermund, and K. Pawelzik
Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution
Advances in Neural Information Processing Systems 15, 2002
PDF, BibTex
M. Bethge and K. Pawelzik
Population Coding with Unreliable Spikes
Neurocomputing, 2002
#population coding
PDF, BibTex

2001


J. Benda, M. Bethge, M. Henning, K. Pawelzik, and A. Herz
Spike-frequency adaptation: Phenomenological model and experimental tests
Neurocomputing, 2001
BibTex
M. Bethge and K. Pawelzik
Synchonous inhibition as a mechanism for unbiased selective gain control
Neurocomputing, 2001
BibTex

1999


M. Bethge, K. Pawelzik, and T. Geisel
Brief pauses as signals for depressing synapses
Neurocomputing, 1999
BibTex
University of Tuebingen BCCN CIN MPI