Electrophysiological Signatures of Distinct Working Memory Subprocesses That Predict Long-term Memory Success (WMLTM)
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Healthy young adults will view pictures of items while the investigators record electroencephalogram (EEG) brain activity. Then, the investigators will ask the participants to report which items the participants remember seeing. The investigators will examine how the measured brain activity relates to which pictures the participants remember.
Full description
Electrophysiological signatures track distinct subprocesses of working memory, including the number of items and the spatial locations of those items. By identifying how these subprocesses predict long-term memory success in healthy young adults, this project should lead to an intricate understanding of the relationship between working memory and long-term memory. This study will investigate when and how long-term memory failures arise, by using sophisticated machine learning analyses of neural data. Moreover, this study will test the extent to which the investigators can track working memory processes in real time and how the investigators can leverage that information to improve long-term memory success. This will inform basic theories of the relationship between working memory and long-term memory and motivate future applications.
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Inclusion criteria
- normal or corrected to normal vision
Exclusion criteria
- non-fluent in English
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Data sourced from clinicaltrials.gov
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