This project will break new ground in the study of memory by partnering with competitors in the USA Memory Championship. These competitors are not savants, but instead are well-practiced in the use of mnemonic techniques and, as a result, exhibit enhanced powers of memory on a range of real-world tasks, such as memorizing the items on a shopping list. All of these techniques rely on the practitioner structuring prior knowledge in very specific ways that facilitate the incorporation of new information. By scanning the brains of these trained memorists with functional magnetic resonance imaging (fMRI) and comparing their brain activity to participants who are learning these mnemonic systems for the first time, the researchers will identify principles for optimal scaffolding: How can prior knowledge be structured and used to most effectively support new learning? Identifying these principles will improve our fundamental understanding of real world-memory and will also lay the foundation for future educational interventions based on these principles. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).
The goal of the project is to extend theories of memory to address how people can optimally use cognitive maps (structured prior knowledge) to support new learning. Reinforcement learning algorithms will be applied to computational models of memory to make predictions about which strategies will result in the best performance, factoring in biological constraints on the human memory system. Model predictions about optimal memory strategies will be tested using fMRI data from memory experts who have spent years optimizing their ability to bind arbitrary information to an internal cognitive map (a ?memory palace?), and who therefore serve as a unique comparison group for optimized memory models; these subjects will be compared to a sample of young adult subjects who are being trained to use these memorization techniques. New neuroimaging approaches developed by the researchers will allow them to map the brain patterns corresponding to each room of the memory palace and the patterns corresponding to each individual memory, and then track the activation of these patterns as subjects recall memories using mental walks through their palace. Results of these analyses will be used to test detailed model predictions about how memory training will alter the structure and use of subjects? cognitive maps, and how these changes relate to memory performance. As a final test of the models, the researchers will use neural measurements of individual subjects? cognitive maps to predict which specific items they will recall. By examining how prior knowledge is deployed to support learning in experts and novices at a much finer resolution than was previously possible, this work will provide the foundation for understanding why wide variations in memory performance exist across individuals and how memory can be improved, paving the way for targeted interventions to improve memory performance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
