Psychology Department, Princeton University
Statistical learning: Detecting, representing, and using regularities in perception
Everyday experience is highly structured: we repeatedly encounter the same people, places, and things, and they tend to appear in reliable spatial and temporal patterns. Learning about these regularities may be a core function of the mind and brain. For example, we readily learn the configuration of objects in a room, the boundaries between words in a language, and the sequence of landmarks on a navigation route. Such statistical learning has been observed across various tasks, in multiple modalities, and throughout development. In a series of behavioral and neuroimaging studies, I will address several key questions about how statistical learning works, including: When are regularities detected? How are they represented as a result of learning? And, how is this knowledge ultimately used? These studies show that statistical learning is powerful and flexible, that it occurs without intent or awareness, and that it has important consequences for other parts of cognition.