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Social Interaction and the Dynamics of Learning

Learning involves time-dependent changes in both local and broadly distributed systems of the brain. At the local level, cognitive processing causes patches of neurons to synchronize their patterns of firing. At the systems-level, when distant parts of the brain cooperate, they exhibit transiently synchronized activation.

Both local and systems-level synchronization are examples of neural dynamics that can be assessed through scalp-recorded measurements of the brain’s electrical activity (electroencephalography or EEG). As part of the initiative to study how neural dynamics constrain learning at the Temporal Dynamics of Learning Center, NSF investigators, Ying Wu and Scott Makeig, are currently investigating how these dynamics change in collaborative and competitive learning contexts. High-density EEG, (128 electrode channels) is recorded simultaneously from two healthy adults as they play a computerized variant of the card game, “Concentration.” A grid of thirty squares is presented to both volunteers on a single touch-sensitive computer screen. Each square is associated with a hidden value, which is briefly revealed when an individual makes contact with the square. Monetary rewards are given whenever a pair of matching values is discovered. In competitive games, players compete with each other to find the greater number of matching pairs. In collaborative games, players work together to find more matching pairs than a computerized competitor. By studying changes in local and systems-level synchronization on successful and unsuccessful turns, it is possible to examine for the first time how social organization affects neural activity during learning. These findings have implications for pedagogy.

Investigators: S. Makeig and Y. Wu, University of California, San Diego