Perception & Action Lab

Statistical learning

The world is a highly structured place with a tremendous amount of statistical structure. Not all objects or events are equally likely to occur – in fact, most physically realizable objects and events almost never occur in our world. The brain uses knowledge of this statistical structure improve performance in a number of ways. It uses statistical knowledge to disambiguate uncertain and ambiguous sensory information, to efficiently code information in working memory and to better perform sensorimotor tasks. Recently, a number of researchers including ourselves have shown that the visual system, and sensory systems in general, do not use static knowledge of environmental statistics, but rather adapts its internal models as the statistics of one's local environment changes (e.g. as you go from your office to the woods). We study how the brain adapts its computations and representations to the changing statistics of visual scenes using both computational models and psychophysical experiments.