Visual Statistical Learning and Perception
Friday, March 02, 2007, 01:00pm - 02:00pm
Yale University, Department of Psychology
Visual statistical learning (VSL) illustrates the ability of the visual system to encode
subtle statistical regularities, without intent or awareness. Work on this topic was
originally motivated by analogous research in language acquisition, and as a result
VSL has remained relatively unconnected to the study of visual perception more generally.
Here we forge such connections, exploring the relationship between VSL and attention,
feature binding, object persistence, and several other factors. We ask about when VSL
occurs, what triggers its onset and offset, what kinds of input it prefers, and what kinds
representations are constructed as a result of such learning. Collectively our results indicate
that VSL is highly constrained by other visual and cognitive processes that may not
themselves be associative in nature. At the same time, these results illustrate the ways in
which VSL may be well adapted to real-world visual cognition. This serves as a case study
of how our visual systems are engaged in intricate types of processing of which we are
not typically aware.
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