From episodic to semantic memory: A computational model

Systems memory consolidation describes the process of transferring and transforming initially hippocampusdependent declarative memories into stable representations in the neocortex. Experimental evidence indicates that neural replay during sleep is linked to this process. While multiple phenomenological theories of systems consolidation have been proposed, a mechanistic theory on the level of neurons and synapses is missing. Here, we study how episodic memories change over time in a recently suggested computational model for the neuronal basis of systems memory consolidation. We implement the proposed mechanism in artificial neural networks and show that memory transfer in the model facilitates the forgetting of episodic detail in memories and enhances the extraction of semantic generalizations. Moreover, we show that neural replay enhances the speed of consolidation and can in certain situations be necessary for the extraction of semantic memories. The latter appears to be the case specifically for the extraction of semantic content from a rapidly learning hippocampal system.