Adaptive Velocity Tuning for Visual Motion Estimation

In the brain, both neural processing dynamics as well as the perceptual interpretation of a stimulus can depend on sensory history. The underlying principle is a sensory adaptation to the statistics of the input collected over a certain amount of time, allowing the system to tune its detectors, e.g. by improving the sampling of the input space. Here we show how a generative formulation for the problem of visual motion estimation leads to an online adaptation of velocity tuning that is compatible with physiological sensory adaptation and observed perceptual effects.