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Statistical learning: detecting, representing, and using regularities in perception

Nicholas Turk-Browne

Monday, October 31, 2011, 12:00pm - 07:00pm

Princeton University, Department of Psychology

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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.


Nicholas Turk-Browne