Have you ever wondered why we are able to negotiate busy traffic intersections or why we are able to find rather quickly the products we need in a busy supermarket? Our visual system is usually overloaded with massive amounts of information, and still we are able to pick up the right information at the right moment in time. Indeed, we should not and cannot pay attention to all events. Instead, we need to direct attention to those events that have proven to be important in the past and suppress those that were distracting and irrelevant. Experiences moulded through a learning process enable us to extract and adapt to the statistical regularities in the world. This process is often referred to as statistical learning. The current project investigates these learning processes determining on how, when and what information is extracted by the visual system. Through brain imaging we seek to understand how learning taking place in brain and this affects attentional representations within putative priority maps across the visual hierarchy. This type of learning is largely unconscious, unintentional, and implicit; it runs "in the background", both seeking and giving structure to the world around us; making it coherent, predictable and quickly manageable. Even though a lot is known about how statistical learning affects language acquisition, object recognition, motor learning, and decision making, the current project is among the first to focus on its role in attention and selection. Visual perception must be selective, as we are confronted with the massive amount of available sensory input. Statistical learning occurring often beneath the level of awareness provides structure to the environment uncovering the relations between objects in space and time.
