Computational Neuroscience

Computational neuroscience is the construction of mathematical models of neural information processing. Because of their inherent complexity, neural circuits need theoretical models which abstract away unnecessary detail and allow us to investigate the crucial aspects of the computation.

Our work has focused largely on the visual system.The approach is to consider how the brain performs a sophisticated statistical and probabilistic analysis of the environment. We analyze the statistical structure of natural images and image sequences. Statistical regularities in the data indicate what kind of features are optimal for processing this data. It happens that the optimal features are, in many cases, very similar to those that the visual cortex is known to compute. These methods also have applications in image processing and computer vision.

See here for a short introduction.

Recently, we have written the first book on this topic, Natural Image Statistics

Research projects: Complex cells and topography, Temporal coherence, V2 and beyond?