A computational model of systems memory consolidation and reconsolidation. Issue 7 (24th December 2019)

• Record Type: Journal Article
• Authors: Helfer, Peter; Shultz, Thomas R.
• Is Part Of: Hippocampus. Volume 30:Issue 7(2020)
• Page Start: 659
• Page End: 677
• Publication Date: 2019-12-24
• Subjects: AMPA receptor exchange -- artificial neural network -- computational model -- memory reconsolidation -- neural plasticity; Hippocampus (Brain) -- Periodicals; 612.825
• DOI: 10.1002/hipo.23187
• Languages: English
• ISSNs: 1050-9631

Abstract

Abstract: In the mammalian brain, newly acquired memories depend on the hippocampus (HPC) for maintenance and recall, but over time, the neocortex takes over these functions, rendering memories HPC‐independent. The process responsible for this transformation is called systems memory consolidation . Reactivation of a well‐consolidated memory can trigger a temporary return to a HPC‐dependent state, a phenomenon known as systems memory reconsolidation . The neural mechanisms underlying systems memory consolidation and reconsolidation are not well understood. Here, we propose a neural model based on well‐documented mechanisms of synaptic plasticity and stability and describe a computational implementation that demonstrates the model's ability to account for a range of findings from the systems consolidation and reconsolidation literature. We derive several predictions from the computational model and suggest experiments that may test its validity.