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Poster C13

Flexible updating of hippocampal representations guides multi-step prediction

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

Hannah Tarder-Stoll1 (, Christopher Baldassano2, Mariam Aly2; 1Rotman Research Institute, 2Columbia University

Our daily lives are temporally structured, enabling prediction of upcoming events. For predictions to be useful, they should be updated when environments change. How does the brain update its predictions in the face of new information? We asked how and when predictive representations change after individuals learn new information about the structure of an environment, focusing on the hippocampus – a region involved in sequence memory and prediction. Participants (N = 32) learned sequences of environments. They then learned novel transitions that linked two previously separate sequences into a single, integrated sequence. During fMRI, participants anticipated upcoming environments one to four steps into the future in the integrated sequence, requiring them to mentally traverse novel transitions to make correct predictions. Participants were able to anticipate using these novel transitions immediately after integration and continued to improve over time, suggesting both rapid and gradual updating of sequence representations. Multivariate fMRI analyses in the hippocampus revealed that representations of the previously separate sequences became more similar after the sequences were linked by new transitions, compared to a no-integration baseline. Importantly, this difference between conditions was strongest for early task runs, suggesting rapid updating of temporal structure in the hippocampus. Finally, hippocampal sequence integration in early runs was related to anticipation performance, particularly on trials in which participants had to mentally traverse the novel transition to make predictions. Overall, this suggests that the hippocampus rapidly updates memory for temporal structure in the service of guiding flexible and adaptive behavior over multiple timescales.

Topic Area: LONG-TERM MEMORY: Episodic


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April 13–16  |  2024