Memory benefits from sleep and these benefits are putatively achieved through reactivation of the neural memory trace during sleep. Studies examining the effects of reactivation commonly focus on single, isolated items - but real-life memories never exist in a vacuum. Individual memories are bound to the context (e.g., the location, time and state of mind in which they are encoded) and this context is later reinstated to recall the details related to the memory. The question of how context participated in the process of sleep reactivation has never been directly examined. This experiment will monitor brain activity during memory encoding, sleep and finally retrieval to investigate the role context plays in sleep-related memory consolidation. Monitoring will be done using functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) recordings. Participants will go through a series of training trials, in which they will have to learn to associate several small images of items or animals with a larger image of scenes - and also learn the spatial location of these smaller images on the screen. The order of the presented images and the scenes in which they are embedded will remain constant throughout training, creating a solid, consistent temporal context in which item memories will be embedded. After training, participants will receive a 90 minute nap opportunity, during which the sounds associated with specific images will be unobtrusively presented. I expect memory for the spatial location of the cued images to improve. Importantly, I hypothesize that this effect will carry over to other items associated with the same scene (i.e., embedded in the same context) and that the temporal order in which the images were learned will govern this effect. I will use the EEG and fMRI data to estimate, on the basis of neuronal pattern activity, the level of contextual reinstatement and will build on these data, in combination with the behavioral results, to model the level of contextual involvement during sleep. These results could pave the way towards a unified theory of sleep's role in memory consolidation, which would encompass computational models of context and memory as well.
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Change in error rates between pre- and post-sleep for the different conditions
Timeframe: Approximately 0.5-1.5 hours before sleep onset and approximately 0.5-1.5 hours after sleep offset within the same experimental session
Results of neural classifier trained to distinguish between different scenes based on blood-oxygen-level-dependent activity
Timeframe: Approximately 1.5 hours before sleep onset and approximately 1.5 hours after sleep offset within the same experimental session
Results of neural classifier trained to distinguish between scenes associated with left/right hand motion based on EEG activity
Timeframe: Approximately 0.5 hours before sleep onset and approximately 0.5 hours after sleep offset within the same experimental session