Abstract
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about the environment. This process is constrained by various factors such as a wide variety of changes in the characteristics of the visual image but also by the necessity to be able to respond as quickly as possible to the incoming sensory stream, for instance to drive a movement of the eyes to the location of a potential danger. To achieve this, it is believed that the visual system takes advantage of the existence of a priori knowledge in the structure of visual information, such as the regularity in the shape and motion of visual objects. We will review different models around the predictive coding coding framework to offer a unified theory to explain many of the mechanisms at the different levels of the visual system and which were unveiled by decades of study in neurophysiology and psychophysics.
Laurent U Perrinet
Researcher in Computational Neuroscience
My research interests include Machine Learning and computational neuroscience applied to Vision.