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State based model of long-term potentiation and synaptic tagging and capture

PLoS Comput Biol. 2009 Jan;5(1):e1000259. doi: 10.1371/journal.pcbi.1000259. Epub 2009 Jan 16.

Abstract

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Electric Stimulation
  • Evoked Potentials
  • Hippocampus / physiology
  • Humans
  • Long-Term Potentiation / physiology*
  • Memory / physiology
  • Models, Neurological*
  • Nerve Net / physiology
  • Nerve Tissue Proteins / metabolism
  • Neurons / metabolism
  • Stochastic Processes
  • Synapses / genetics
  • Synapses / metabolism
  • Synaptic Transmission / physiology*

Substances

  • Nerve Tissue Proteins