Bandpass filtering, orientation selectivity, and contrast gain control are prominent features of sensory coding at the level of V1 simple cells. While the effect of bandpass filtering and orientation...
Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing (2009)
Bridle, Sarah, Balan, Sreekumar T., Bethge, Matthias, Gentile, Marc, Harmeling, Stefan, Heymans, Catherine, ...
We present the results of the GREAT08 Challenge, a blind analysis challenge to infer weak gravitational lensing shear distortions from images. The primary goal was to stimulate new ideas by...
Natural Image Coding in V1: How Much Use is Orientation Selectivity? (2008)
Eichhorn, Jan, Sinz, Fabian, Bethge, Matthias
Orientation selectivity is the most striking feature of simple cell coding in V1 which has been shown to emerge from the reduction of higher-order correlations in natural images in a large variety of...
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior (2008)
Sebastian Gerwinn, Jakob H Macke, Matthias Seeger, Matthias Bethge
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation...
Matthias Bethge, Sebastian Gerwinn, Jakob H. Macke
learning of a steerable basis for invariant image representations
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images (2008)
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer from their poor...
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images (2008)
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer from their poor...
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior (2008)
Sebastian Gerwinn, Jakob H Macke, Matthias Seeger, Matthias Bethge
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation...
The Independent Components of Natural Images are Perceptually Dependent (2008)
Matthias Bethge, Thomas V. Wiecki, Felix A. Wichmann
The independent components of natural images are a set of linear filters which are optimized for statistical independence. With such a set of filters images can be represented without loss of...
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior (2008)
Gerwinn, Sebastian, Macke, Jakob, Seeger, Matthias, Bethge, Matthias
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation...
Bayesian Inference for Sparse Generalized Linear Models (2007)
Seeger, Matthias, Gerwinn, Sebastian, Bethge, Matthias
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The parameters can be endowed...
Bayesian inference for sparse generalized linear models (2007)
Matthias Seeger, Sebastian Gerwinn, Matthias Bethge
Abstract. We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The parameters can be...
The performance of unsupervised learning models for natural images is evaluated quantitatively by means of information theory. We estimate the gain in statistical independence (the multi-information...
of Neuronal Representations (2003)
Matthias Bethge, Vom Fachbereich, Doktor Der Naturwissenschaften, Matthias Bethge, Yara Lena, ...
Whenever one draws conclusions from data of neuronal activity about its function for sensory processing and generating behavior, one inevitably has to hypothesize about the neural code. Moreover,...
Matthias Bethge, Klaus Pawelzik
The need for a neuronalcodin scheme thati robust agaitb the corruptiS ofactix potentiS[ seems to support the ieb ofpopulati[ ratecodix` where the relevance of asi17` spi7 decreases proportixR[ to...
Binary Tuning is Optimal for Neural Rate (2002)
Coding With High, Matthias Bethge, David Rotermund, Klaus Pawelzik
Here we derive optimal gain functions for minimum mean square reconstruction from neural rate responses subjected to Poisson noise. The shape of these functions strongly depends on the length of the...
Synchonous inhibition as a mechanism for unbiased selective gain control (2001)
Matthias Bethge, Klaus Pawelzik
While there are many experiments providing evidence for synchronized neuronal activity, there is little agreement about its functional role. Since many proposals rely on the assumption that neuronal...
Author Tel Mailaddres, Matthias Bethge, Klaus Pawelzik
While there are many experimentsproviding evidence for synchronized neuronal activity, there is littleagtleMIE about its functional role. Since many proposals rely on the assumption that neuronal...
Brief Pauses as Signals for Depressing Synapses (1999)
Matthias Bethge, Klaus Pawelzik, Theo Geisel
Activity-dependent synaptic depression is a striking feature of synaptic transmission between neocortical pyramidal neurons. It has been shown that this kind of synaptic dynamics permits the...
Corresponding author. Tel.: 49-421-218-3645; fax: 49-421-218-9104. (1999)
Mail Address Pawelzik, Matthias Bethge, Klaus Pawelzik, Theo Geisel
Activity-dependent synaptic depression is a striking feature of synaptic transmission between neocortical pyramidal neurons. It has been shown that this kind of synaptic dynamics permits the...
Natural Image Coding in V1: How Much Use Is Orientation Selectivity?
Eichhorn, Jan, Sinz, Fabian, Bethge, Matthias
Orientation selectivity is the most striking feature of simple cell coding in V1 that has been shown to emerge from the reduction of higher-order correlations in natural images in a large variety of...
Characterization of the p-generalized normal distribution
Sinz, Fabian, Gerwinn, Sebastian, Bethge, Matthias
It is a well known fact that invariance under the orthogonal group and marginal independence uniquely characterizes the isotropic normal distribution. Here, a similar characterization is provided for...