Self-organized reactivation maintains and reinforces memories despite synaptic turnover
Abstract
Long-term memories are believed to be stored in the synapses of cortical neuronal networks. However, recent experiments report continuous creation and removal of cortical synapses, which raises the question how memories can survive on such a variable substrate. Here, we study the formation and retention of associative memory in a computational model based on Hebbian cell assemblies in the presence of both synaptic and structural plasticity. During rest periods, such as may occur during sleep, the assemblies reactivate spontaneously, reinforcing memories against ongoing synapse removal and replacement. Brief daily reactivations during rest-periods suffice to not only maintain the assemblies, but even strengthen them, and improve pattern completion, consistent with offline memory gains observed experimentally. While the connectivity inside memory representations is strengthened during rest phases, connections in the rest of the network decay and vanish thus reconciling apparently conflicting hypotheses of the influence of sleep on cortical connectivity.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. The source code zip archive (Source code 1) contains the model simulation code and the stimulation file used to generate Figure 2, 3, 4B&C, 5 and 6 as well as Figure 4-figure supplements 1 and 2.
Article and author information
Author details
Funding
Deutsche Forschungsgemeinschaft (FA 1471/1-1 and 2-1)
- Michael Jan Fauth
Engineering and Physical Sciences Research Council (EP/R030952/1)
- Mark CW van Rossum
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Fauth & van Rossum
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,719
- views
-
- 570
- downloads
-
- 67
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 67
- citations for umbrella DOI https://doi.org/10.7554/eLife.43717