NCS-FO: Collaborative Research: Sleep's role in determining the fate of individual memories

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Identifying the cognitive, computational and neural mechanisms responsible for determining why some memories survive when others fade is one of the many grand challenges facing researchers of the human mind and brain. It is widely understood that sleep plays a critical role in long-term remembering, yet what exactly happens during sleep to affect the persistence of memories remains largely unknown. This project brings together a team of researchers who will integrate multiple independent lines of work in cognitive neuroscience, cognitive psychology, and computer science in order to investigate the precise mechanisms undergone by recently-formed memory representations as a person sleeps and how these mechanisms determine which memories survive and which fade. The proposed integration of cutting-edge neural data analysis methods for EEG and neuroimaging data, basic human memory theory, and neural network modeling make possible the ability to non-invasively track individual memories in the human brain as they compete with each other and are modified during sleep. The potential advances from this work could impact education, training situations, and public health by facilitating the development of new strategies for ensuring that important memories survive after initial learning.Research suggests that memories compete for neural space such that reactivating one particular memory can exert "collateral damage" on other related memories. In other words, accessing one memory can come at the expense of later being able to access other nearby memories in the network space. The proposed studies test the hypothesis that importance shapes neural dynamics during sleep by selectively boosting memory reactivation; this boost ensures that important memories out-compete related memories during sleep, resulting in strengthening of important memories and weakening of less-important memories. To test this hypothesis, competition between memories will be elicited during sleep by playing sound cues, each of which was linked (during wake) to two different picture-location memories. Multiple interlocking approaches will track how memory competition during sleep shapes a memory's persistence versus fading. Neural network models will be used to generate predictions about how reward responses during encoding shape competitive dynamics during sleep, and how these competitive dynamics determine the eventual fates of competing memories. Predictions will be tested by using fMRI to measure neural activity associated with reward processing during encoding, EEG to measure brain activity during sleep, and pattern classifiers to decode memory activation from the sleep EEG data. Observations of competitive dynamics during sleep will then be related to later memory performance and to multivariate fMRI measures of memory change. The project has the potential to provide, for the first time, a comprehensive look "under the hood" at the life of a memory as it is acquired, processed during sleep, and eventually recalled. Pivotal knowledge will be gained about how variance in reward processing at encoding influences sleep replay dynamics, and about how sleep replay dynamics affect subsequent memory performance and the structure of neural representations.