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Nicholas B. Turk-Browne, Marcia K. Johnson, Marvin M. Chun, Brian J. Scholl; Neural evidence of statistical learning: Incidental detection and anticipation of regularities. Journal of Vision 2008;8(6):695. doi: 10.1167/8.6.695.
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© 2017 Association for Research in Vision and Ophthalmology.
Our environment contains many regularities distributed in space and time that can be detected by way of statistical learning. This unsupervised learning occurs without intent or awareness, but little is known about its component processes, how it manifests over time, or how it relates to other types of learning. Here we use fMRI as a measure of statistical learning to explore these questions. Participants viewed short blocks of novel shapes appearing one at a time, while performing a motion-detection cover task. The underlying sequence of shapes constituted our primary manipulation. Structured blocks contained deterministic sub-sequences of shapes. Random blocks lacked this structure but were otherwise identical. Sensitivity to statistical structure was assessed by comparing fMRI responses to these two block types. This approach resulted in several discoveries about the nature of statistical learning. (1) Robust neural responses to statistical structure were observed during learning, despite weak subsequent explicit familiarity judgments – indicating the utility of fMRI as a measure of statistical learning. (2) This neural evidence of learning emerged after surprisingly little exposure – as made possible by our use of an online measure of learning. (3) The brain regions that were sensitive to statistical structure overlapped with those underlying other well-studied forms of learning and memory – helping to characterize the nature of the component processes that support statistical learning. (4) Responses to statistical structure were also observed in visual cortical regions – suggesting that these regions are sensitive to temporally contiguous relations in addition to static visual features. (5) Several regions involved in reflective processing exhibited enhanced responses to the beginnings of deterministic subsequences – suggesting that anticipation per se need not be conscious, and may be a natural perceptual process. Collectively, these results emphasize both the power of statistical learning and its integration with other cognitive processes.
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