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DC Field | Value | Language |
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dc.contributor | Norman, Kenneth | - |
dc.contributor.advisor | Daw, Nathaniel | - |
dc.contributor.author | Rhee, Eeh Pyoung | - |
dc.date.accessioned | 2016-07-14T15:13:04Z | - |
dc.date.available | 2017-07-01T08:05:45Z | - |
dc.date.created | 2016-04-29 | - |
dc.date.issued | 2016-07-14 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01sx61dp75b | - |
dc.description.abstract | While studies have shown the importance of offline memory reactivation during rest to memory consolidation, how these offline mechanisms and memory interact to facilitate learning is less clear. Other studies have shown behaviorally that interference during rest interferes with learning, but no neuroimaging study has shown the connection between rest period memory replay and learning. In this paper, we analyzed functional MRI data from 24 subjects to assess the effect of memory replay during rest periods when a re-learning of the existing model of the world is required. We find that the degree of memory replay from rest periods is predictive of subjects’ performances in future tasks that require novel inferences, and find that this replay is functionally associated with other regions of the brain that have been shown to be active in memory integration. These findings support a framework of human learning that incorporates an offline replay mechanism where an existing model is updated by new experiences. Supplementary Material and Code can be found at: https://github.com/sarcastic999/ReplayRevaluationThesis 2 | en_US |
dc.format.extent | 44 pages | * |
dc.language.iso | en_US | en_US |
dc.title | Memory Replay During Rest Facilitates Learning: an fMRI Study | en_US |
dc.type | Princeton University Senior Theses | - |
pu.embargo.terms | 2017-07-01 | - |
pu.date.classyear | 2016 | en_US |
pu.department | Computer Science | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
Appears in Collections: | Computer Science, 1988-2020 |
Files in This Item:
File | Size | Format | |
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Rhee_Eeh_Pyoung_2016_Thesis.pdf | 1.02 MB | Adobe PDF | Request a copy |
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