# Neural-network simulations of memory consolidation and reconsolidation

## TL;DR

This paper presents a neural network model simulating how memories are initially dependent on the hippocampus and later transferred to the neocortex, including the effects of reactivation on hippocampal dependence.

## Contribution

It introduces a computational model that incorporates recent synaptic plasticity mechanisms to explain and predict memory consolidation and reconsolidation processes.

## Key findings

- Model replicates hippocampus-dependent memory initially
- Reactivation induces temporary hippocampal dependence
- Predicts specific synaptic changes during consolidation

## Abstract

In the mammalian brain newly acquired memories depend on the hippocampus for maintenance and recall, but over time these functions are taken over by the neocortex through a process called systems consolidation. However, reactivation of a consolidated memory can induce a brief period of temporary hippocampus-dependence, followed by return to hippocampus-independence. Here we present a computational model that uses simulation of recently described mechanisms of synaptic plasticity to account for findings from the systems consolidation/reconsolidation literature and to make predictions for future research.

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Source: https://tomesphere.com/paper/1901.02270