ABSTRACT
SMRITI is a computational model of episodic memory that demonstrates how a cortically expressed transient pattern of activity representing an episode can be transformed rapidly into a persistent and robust memory trace in the hippocampal system (HS) as a result of long-term potentiation. The neural circuit required for encoding an episodic memory trace is fairly complex and idiosyncratic, but SMRITI shows that this complexity and idiosyncrasy is well matched by the complexity and idiosyncrasy of the architecture and local circuitry of the HS. SMRITI also offers biologically grounded explanations of behavioral findings about human memory such as the fan-effect and the list-strength effect. SMRITI makes specific behavioral predictions about the time required for retrieving memorized facts. SMRITI also predicts that retrieval times of facts pertaining to populated event schemas are qualitatively different from those of facts pertaining to unpopulated ones.
