Hippocampo-neocortical interaction as compressive retrieval-augmented generation
This paper proposes a computational model that frames hippocampo-neocortical interaction as a compressive retrieval-augmented generation system, where the hippocampus stores and retrieves compressed episodic memories to guide a neocortical network in extracting generalizable semantic patterns for memory reconstruction and problem solving.