PROJECT SUMMARY Visual working memory is a central cognitive system for maintaining active representations about currently relevant information. Individual differences in working memory ability reflect a core cognitive ability, as shown by robust correlations with fluid intelligence, scholastic achievement and other broad measures of intellectual function. Furthermore, working memory deficits are a signature of many prevalent mental health disorders, such as attention deficit/ hyperactivity disorder (ADHD), schizophrenia and depression. Thus, a detailed understanding of this system is important for understanding the cognitive effects of these disorders, and for precise assessments of the efficacy of clinical interventions. The broad goal of this proposal is to enhance our understanding of the neural signals that index storage in this online memory system, and to use those signals to refine cognitive models of human memory. A key recent discovery is that the electrophysiological signals that index storage in working memory can be divided into two distinct categories. One class of activity tracks the number of discrete “items” or objects that are stored in working memory, without regard to the specific information associated with each object. A second class of activity instead tracks the spatial positions that are currently prioritized in the visual field, without regard to the number of independent objects occupying those positions. The proposed work will pursue this insight, refining both neural and cognitive models of human working memory. Finally, while working memory plays a critical role in complex cognition, there is a clear consensus that working memory must interact with qualitatively different memory systems (e.g., long term memory) that store information “offline” or out of mind. While past work has often sought paradigms that allow a “pure” assessment of working memory or long term memory, there is a strong need for work that directly examines the dynamic collaboration between these systems. Thus, a central theme of this project will be to identify the specific factors that encourage transitions between online and offline memory states. Specifically, the proposal will follow up on past work showing that observers divide up ongoing continuous experiences into discrete “event” representations, and that the boundaries between events influence which pieces of information are integrated and segregated in memory. This project will use time-resolved electrophysiological measures of storage in working memory to determine whether event boundaries prompt the flushing of online memories to make way for information about subsequent events, even when there is adequate capacity for concurrent storage. This will provide new insight into the specific cognitive operations that determine how limited online memory capacity is deployed in complex cognitive tasks.