Statistical Learning and Its Consequences
Statistical learning refers to an unconscious cognitive process in which repeated patterns, or regularities, are extracted from the sensory environment. In this chapter, I describe what is currently known about statistical learning. First, I classify type
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Abstract Statistical learning refers to an unconscious cognitive process in which repeated patterns, or regularities, are extracted from the sensory environment. In this chapter, I describe what is currently known about statistical learning. First, I classify types of regularities that exist in the visual environment. Second, I introduce a family of experimental paradigms that have been used to study statistical learning in the laboratory. Third, I review a series of behavioral and functional neuroimaging studies that seek to uncover the underlying nature of statistical learning. Finally, I consider ways in which statistical learning may be important for perception, attention, and visual search. The goals of this chapter are thus to highlight the prevalence of regularities, to explain how they are extracted by the mind and brain, and to suggest that the resulting knowledge has widespread consequences for other aspects of cognition. Keywords Regularities · Memory systems · Perception · Selective attention · Generalization · fMRI
Introduction Human behavior is often geared towards one object at a time, as in picking up a coffee mug, recognizing a friend’s face, or noticing a car’s age. This fact is even more apparent in visual search, where we typically seek one target object among other distracting objects: looking for my coffee mug among many others in the office lounge; trying to track down a particular friend at a cocktail party; or, searching for my car in an airport parking garage. How we succeed (and fail) in these kinds of searches is the topic of the 59th Nebraska Symposium, including critical factors such as attention, memory, reward, and real-world complexities. The purpose of this chapter is to highlight another important factor in visual search, ‘statistical learning’. N. B. Turk-Browne () Department of Psychology, Princeton University, Green Hall, Princeton, NJ 08540, USA e-mail: [email protected]
M. D. Dodd, J. H. Flowers (eds.), The Influence of Attention, Learning, and Motivation on Visual Search, Nebraska Symposium on Motivation, DOI 10.1007/978-1-4614-4794-8_6, © Springer Science+Business Media New York 2012
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Although the goal of visual search is to find a target object, we rarely need to start from scratch. Rather, we can use knowledge about when and where this object appears relative to other objects to find what we’re looking for. In the searches above, for example, I may know from prior experience that my coffee mug sits on top of a shelf rather than floating in air; that my friend hangs out with certain people who may also be at the party; and, that I tend to park near the elevator in parking garages. Indeed, we repeatedly come across the same people, places, and things, and over time they tend to appear in similar spatial configurations and temporal sequences. Statistical learning is an unconscious process by which we extract these patterns (or ‘regularities’) in how objects appear relative to each other in the visual environment.
Statistical Regularities in
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