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Sleep is known to be an important time for consolidating our memories, with memory systems in the brain replaying recent memories and stabilizing them for long-term storage. We present a computational model that simulates these interactions between hippocampal and neocortical memory systems, providing an account of how they can autonomously produce useful offline learning. We explain how information stored initially in the hippocampus can help to build neocortical representations during sleep, and how the alternation of different stages of sleep across the night can facilitate graceful integration of new information with existing knowledge.

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This page is a summary of: A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation, Proceedings of the National Academy of Sciences, October 2022, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2123432119.
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