Statistical learning and its consequences.

Nicholas B. Turk-Browne

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)117-146
Number of pages30
JournalNebraska Symposium on Motivation. Nebraska Symposium on Motivation
StatePublished - Dec 1 2012

All Science Journal Classification (ASJC) codes

  • Social Psychology


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