http://tdlc.ucsd.edu/research/DNS/speakers/Schapiro.html Anna Schapiro received her B.S. from Stanford University in Symbolic Systems and Ph.D. from Princeton University in Psychology and Neuroscience. She is currently a Postdoctoral Fellow at Harvard Medical School. Her research draws on neuroimaging, behavioral, and computational modeling techniques to investigate the learning of novel structured information and its consolidation during sleep. Dr. Anna Schapiro will be presenting on the “Complementary learning systems within the hippocampus.” There is a fundamental tension in memory between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting regularities across these experiences, which supports generalization and prediction in similar situations in the future. These two types of memory are at odds because storing discrete, separated episodes hinders identification of relationships across the episodes, while representing regularities blurs idiosyncratic details. This computational tension is solved in the classic Complementary Learning Systems theory by proposing that episodic memory and statistical learning are separated anatomically: the hippocampus rapidly encodes episodes, while the cortex slowly extracts regularities over days, months, and years. This account fails, however, to explain our ability to learn statistics quickly — within a few minutes or hours. I will present evidence from fMRI and patient studies suggesting that in addition to its well-established role in episodic memory, the hippocampus is responsible for rapid statistical learning. But how can these two opposing processes coexist in one brain structure? Using a neural network model of hippocampal projections and subfields, I demonstrate a natural division of labor across different known anatomical pathways within the hippocampus. These simulations suggest that there are complementary learning systems operating within the hippocampus itself that allow it to remember both individual episodes and the regularities that hold across them.