State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture

By Adam B. Barrett, Guy O. Billings, Richard G. M. Morris, M. V. Rossum. 2009

93 citations recorded by the source corpus.

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.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Synaptic weight decay with selective consolidation enables fast learning without catastrophic forgetting (2019, methodology): “We suggest a normative theory of synaptic consolidation that functionally reproduces the phenomena of the multi-state models of tagging & capture (Barrett et al., 2009; Clopath et al., 2008; Ziegler et al., 2015).”
Computational principles of synaptic memory consolidation (2016, background): “Although we discussed the case in which only u 1 is read out, our model can be extended to the case in which more than one dynamical variable determines the synaptic efficacy (see also Supplementary Note 5 ).”
The dendritic branch is the preferred integrative unit for protein synthesis-dependent LTP (2011, methodology): “…and branch bias of STC are incompatible with somatic synthesis of PrPs and their subsequent redistribution throughout the dendritic arbor (Barrett et al., 2009; Clopath et al., 2008; Frey, 2001; Frey and Morris, 1997; Okada et al., 2009) unless one assumes the existence of an extra…”
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules (2016, background): “If a neuromodulatory signal (green arrows, top) arrives, the synapses with raised flags undergo plasticity (top: synapses of medium strength before phasic neuromodulatory signal; bottom: synapses after change).”
Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules (2018, background): “Hebbian models of synaptic consolidation have several hidden flag variables (Fusi et al., 2005; Barrett et al., 2009; Benna and Fusi, 2016) but can also be situated as examples within the general framework of Hebbian rules.”
Memory retention and spike-timing-dependent plasticity. (2009, background): “Third, in classical LTP different stimulus strengths and paradigms activate different biochemical plasticity pathways, resulting in varying LTP longevity, see e.g., (Abraham 2003; Barrett et al. 2009), and similar effects have been observed in sensory plasticity (Zhou et al. 2003).”
Computational models of long term plasticity and memory (2017, methodology): “Phenomenological models [Clopath et al., 2008, Barrett et al., 2009, Ziegler et al., 2015] of STC comprise all four steps, and can explain experiments on the induction of protein synthesis dependent late LTP.”
Making memories last: the synaptic tagging and capture hypothesis (2010, background): “From a computational perspective, the concept provides a new way of thinking about synaptic potentiation in which the various 'states' of a synapse reflect both the current level of synaptic strength and the potential of the synapse for lasting changes in strengt”
Synaptic Consolidation: From Synapses to Behavioral Modeling (2015, background): “Although previous models of consolidation (Clopath et al., 2008; Barrett et al., 2009; Smolen et al., 2012) were able to account for the above results, experiments on tag resetting (Sajikumar and Frey, 2004a) remained unexplained.”