State based model of long-term potentiation and synaptic tagging and capture.
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.
Barrett
Adam B
AB
Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk
Billings
Guy O
GO
Morris
Richard G M
RG
van Rossum
Mark C W
MC
D000818:Animals; D004558:Electric Stimulation; D005071:Evoked Potentials; D006624:Hippocampus / Q000502:physiology; D006801:Humans; D017774:Long-Term Potentiation / Q000502:physiology*; D008568:Memory / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009419:Nerve Tissue Proteins / Q000378:metabolism; D009474:Neurons / Q000378:metabolism; D013269:Stochastic Processes; D013569:Synapses / Q000235:genetics / Q000378:metabolism; D009435:Synaptic Transmission / Q000502:physiology*
D009419:Nerve Tissue Proteins