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Visual-Spatial Working Memory

Pilots keep track of a dizzying amount of visual information while operating commercial and military aircraft. Air traffic controllers on the ground must remember the contents of their radar displays while executing multiple peripheral tasks. Automobile drivers must remember the positions of other cars on the road while planning their route and attending to road signs and traffic lights. In order to do these tasks, humans must have cognitive mechanisms for storing and maintaining a consistent mental representation of the environment as it changes. These mechanisms are referred to as visual-spatial working memory (VSWM).

Our research uses several experimental procedures to understand how information is stored and updated in VSWM.

• Dropper is our code-name for a dynamic object arrangement task which allows us to study the interaction between memory and performance under laboratory conditions. It is a simplified analog to air-traffic control tasks.
• In the change-detection procedure, people have to remember a briefly presented visual display in order to compare it to a second display and detect any differences between the two. This procedure simulates real-world tasks in which people have to remember visual information while performing other tasks that force them to look away from their main task. It turns out that people can remember a fairly limited amount of information, but they store it in an efficient and structured form.
• In the cued object-identification procedure, people have to remember briefly presented visual displays of colored shapes (e.g., a red circle and blue square) so that they can recall the color when we verbally cue one of the shapes (e.g., if we say "square", they have to say "blue").

As with other projects in this lab, our understanding of VSWM is inspired by careful data-analysis and computational modeling using the EPIC architecture.

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