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Humans live a cognitively constrained existence. At any one time, we can only choose from a small set of cognitive operations and process a fraction of our experiences. Nevertheless, our memory system demonstrates remarkable adaptability in navigating a complex and partially known world. What are the exact forms of the cognitive constraints in memory and their neural basis? How does our memory system optimize its performance within these constraints? Our lab combines computational modeling, behavioral methods, and neural imaging to address these questions.
Understanding the mechanisms behind optimal memory provides a theoretical framework for explaining why memory succeeds in some instances or individuals but fails in others, and makes it possible in future work to devise targeted interventions to enhance memory. Moreover, by elucidating how humans optimally encode and retrieve information, as implemented in mathematically transparent theories, we can potentially inform the design and provide better understanding of AI systems that rely on intelligent use of memory.