Synaptic reentry reinforcement based network model for long-term memory consolidation.

The conversion of newly formed declarative memories into long-term memories is known to be dependent on the hippocampus. Recent experiments suggest that memory consolidation requires reactivation of the NMDA receptor in CA1 during the initial week(s) after training. This led to the hypothesis that the repeated post-learning reinforcement of synaptic modifications, termed synaptic reentry reinforcement (SRR), is essential for long-term memory consolidation and storage. Based on experimental observations, we have built a computational model to further illustrate and explore the effect of the SRR process on the formation of long-term memory. We show that SRR is capable of strengthening and maintaining memory traces despite inherent variability in the system due to such processes as the turnover of synaptic receptors and their associated signaling and structural proteins. Furthermore, we demonstrate that new rounds of synaptic modification triggered by memory reactivation, either during conscious recall or sleep, could lead to the selective consolidation of a subset of memory traces. Finally, we show why the SRR process in the hippocampus is required during the initial post-training weeks for synaptic reinforcement based memory consolidation in the cortex.