Tracking the dynamics of how schemas scaffold recall - Project Summary
Every new experience in our life takes place within the context of familiar environments and situations. However,
most research on memory has focused on the artificial memorization of word lists, symbols or pictures; these
studies do not meaningfully address how structured prior knowledge about the world (e.g., in the form of a familiar
spatial map, or knowledge of how restaurant meals unfold over time) can scaffold new learning. In the proposed
studies, I aim to precisely characterize how and where prior knowledge and new information are
represented, how they get linked at encoding, and how they interact at recall to allow memories to be
retrieved. In the first proposed study of my F99 phase, I test the hypothesis that hippocampal engagement at
event boundaries during learning binds new information (i.e. objects) to the scaffold of existing knowledge (i.e.
knowledge of a familiar location), and that hippocampal activation during recall mediates the successful retrieval
of the bound object from the location in which it was stored. I also test the hypothesis that distinctive
representations of spatial locations in the brain will reduce interference between objects stored in those locations.
There is a potential downside to using prior knowledge as a scaffold: When there is too much information
attached to one part of the scaffold, old and new memories will interfere with each other. How, then, could
someone prioritize the retrieval of new memories over older (now-irrelevant) memories that were linked
to the scaffold? Recent research on intentional forgetting suggests a solution to this limitation. Specifically, in
my second proposed study, I test the hypothesis (supported by neurophysiological evidence, prior
neuroimaging results, and computational models) that previously encoded memories can be weakened by
moderately activating their neural representation, thereby “cleaning” the scaffold and reducing interference. In
the K00 phase, I will extend my research to identify pathologies in how clinical populations use prior knowledge
to interpret and remember their experiences, using tools from computational psychiatry; I also plan to design
new technological tools to address these issues. Overall, the proposed project makes use of naturalistic
and ecologically valid stimuli (in the form of continuous stimuli and immersive virtual reality) paired with
advanced machine learning tools applied to brain imaging data, to study the fundamental nature of how
new and old information are linked to allow learning. In the long-term, the findings from this project regarding
how prior knowledge can be optimally leveraged to support new learning will lead to the development of tools to
help memory-impaired individuals make better use of prior knowledge to support new learning, as well as
remedies for groups where deficiencies in prior knowledge prevent them from learning properly.