Matthias Bethge

Publications, Email, Homepage, Phone: +49 7071 29 89017
Group Leader
My research goal is to understand how the brain makes sense of its high-dimensional sensory input. In particular, I seek to understand the formation of distributed neural representations in the early visual system by studying natural image statistics, unsupervised learning, and neural population coding, and by developing new data-analysis tools.

Heike König

Email, Phone: +49 7071 29 89018

Judith Lam

Email, Homepage, Phone: +49 7071 29 89019
Bernstein Coordinator
At the Bernstein Center Tübingen, scientists from various disciplines, including theoretical and experimental neurobiology, machine learning, and medicine, collaborate in order to analyze the basis of inference processes in the brain. In particular, a main research goal is to understand the coordinated interaction of neurons during information processing.

Philipp Berens

Publications, Email, Homepage, Phone: +49 7071 29 88910
Project Leader
I use machine learning to study the diversity of cell types in the retina and the visual cortex, the circuits they form and how they perform visual computations. To this end, I work closely with the lab of Thomas Euler at the CIN/Tübingen and with the lab of Andreas Tolias at BCM/Houston. In addition, I teach statistics and neural data analysis at the Graduate School for Neural Information Processing.

Wieland Brendel

Publications, Email, Phone: +49 7071 29 88906

Alexander Ecker

Publications, Email, Phone: +49 7071 29 88908
The goal of my research is to understand how populations of neurons interact to process visual information. I combine multi-electrode recordings in primary visual cortex of monkeys with theoretical approaches to study population coding.

Alexander Mathis

Publications, Email, Homepage
I am a Marie Curie fellow in the lab of Professor Venkatesh Murthy at the Department of Molecular and Cellular Biology at Harvard University and with Professor Matthias Bethge at the Bernstein Center for Computational Neuroscience at the University of Tuebingen. My main research interests comprise active sensing, odor-guided navigation and optimal coding.

Tom Wallis

Publications, Email, Homepage
How do we visually experience the world around us in a coherent way, simply from the patterns of photons hitting our retinae? While it seems effortless to us, the formation of this representation by the brain is decidedly difficult to explain. I am working with Prof. Bethge and Prof. Felix Wichmann investigating the mechanisms of visual representation using psychophysics and computational modelling.

Christian Behrens

Publications, Email
Graduate Student
I work on neural coding in the retina and data analysis.

Alexander Böttcher

Publications, Email, Phone: +49 7071 29 88905
Graduate Student
My aim is to understand how the activity of sensory neurons leads to decisions taken by the brain. In particular, I am interested in neural population coding of the primary somatosensory cortex.

Leon Gatys

Publications, Email, Phone: +49 7071 29 88907
Graduate Student
Deep convolutional neural networks are the first artificial systems that rival biology in terms of difficult perceptual inference tasks such as object recognition. At the same time, their hierarchical architecture and basic computational properties admit a fundamental similarity to real neural systems, making them compelling candidate models for studying visual information processing in the brain. Thus in my PhD project I seek to infer the neural organisation of visual perception from high-performing convolutional neural networks.

Matthias Kümmerer

Publications, Email, Phone: +49 7071 29 88909
Graduate Student
Learning what properties of an image are associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. Recent advances in deep learning for the first time enable us to explain a significant portion of the information expressed in the spatial fixation structure. My interest is twofold: I want to create better models for predicting human fixations in different tasks and on the other hand make use of these models to increase our understanding of how humans perform this task from a neuroscientific and psychophysical standpoint.

Lucas Theis

Publications, Email, Homepage, Phone: +49 7071 29 88910
Graduate Student
A lot of evidence from theoretical considerations and biological observations points to the fact that a good representation for natural images should be hierarchically organized. Yet, the best known models of natural images are based on what is better described as shallow representations. My research aims at resolving this discrepancy by finding better strategies for capturing the regularities found in natural images in a hierarchical manner.

Santiago Cadena

Research Assistant

Debapriya Das

Email, Phone: +49 7071 29 88906
Research Assistant

Jonas Rauber

Email, Homepage
Research Assistant

Ivan Ustyuzhaninov

Research Assistant
University of Tuebingen BCCN CIN MPI