An important, yet relatively unexplored aspect of learning and working memory is how, and under what conditions, a perceiver can capitalize on regularities in the environment to remember more information. How can our prior experiences influence how we remember our current experiences? How can such influences be exploited as tools to enhance cognitive processes in those with learning disabilities (e.g., in Autism), or to assist those with memory deficits? To address these issues, this proposal makes use of a powerful form of implicit learning known as visual statistical learning. Previous research has shown that observers are extremely sensitive to regularities in the visual environment (e.g., quickly learning that 'A'is usually followed by 'B'). Surprisingly, this learning is often completely implicit: when asked to explicitly report these regularities observers perform at chance. This implies that visual statistical learning is a powerful process that operates automatically without our intent or conscious control. However, it remains unclear what the benefits of visual statistical learning are for memory processes. In particular, statistical regularities are a form of redundancy, and to the extent that human memory compresses redundant information, learning regularities between objects should enable observers to remember information about more objects. The proposed experiments have three aims: (1) to determine whether visual statistical learning enables observers to compress information and remember more, (2) to determine the """"""""units"""""""" of compression, and (3) to determine the """"""""level"""""""" at which compression occurs. To investigate these issues, observers will be required to remember simple objects. Over time, some observers will see patterns in the input (e.g., 'A'often occurs with 'B'), while other observers will see random input. To the extent that observers can learn regularities, and compress them to form more efficient memory representations, observers in the patterned group should remember details about more objects. Previous research has not directly explored how visual statistical learning impacts the capacity of working memory, and the proposed studies will provide important insight into the interactions between learning and memory.

Public Health Relevance

An exciting aspect of this proposal is that it promises to inform basic science by studying how statistical learning impacts working memory and cognition, and therefore has potential to increase understanding of mental illnesses with learning or memory related symptoms. For instance, individuals with Autism have certain learning deficits, but it is unknown whether statistical learning, and its interaction with working memory, is impaired in Autism as well. The proposed studies lay the groundwork for future clinical translational research addressing such questions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Small Research Grants (R03)
Project #
5R03MH086743-02
Application #
8036060
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Osborn, Bettina D
Project Start
2010-03-01
Project End
2012-01-31
Budget Start
2011-02-01
Budget End
2012-01-31
Support Year
2
Fiscal Year
2011
Total Cost
$84,000
Indirect Cost
Name
Harvard University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
02138
Fougnie, Daryl; Suchow, Jordan W; Alvarez, George A (2012) Variability in the quality of visual working memory. Nat Commun 3:1229
Brady, Timothy F; Konkle, Talia; Alvarez, George A (2011) A review of visual memory capacity: Beyond individual items and toward structured representations. J Vis 11:4
Brady, Timothy F; Alvarez, George A (2011) Hierarchical encoding in visual working memory: ensemble statistics bias memory for individual items. Psychol Sci 22:384-92