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

• Main Authors: Adam B Barrett, Guy O Billings, Richard G M Morris, Mark C W van Rossum
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2009-01-01
• Series: PLoS Computational Biology
• Online Access: https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19148264/?tool=EBI

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.