ArticleFrontiers in computational neuroscience2010
Postsynaptic signal transduction models for long-term potentiation and depression.
Article in Frontiers in computational neuroscience, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Stable continual learning through structured multiscale plasticity manifolds.Current opinion in neurobiology · 2021Review
- Online Learning and Memory of Neural Trajectory Replays for Prefrontal Persistent and Dynamic Representations in the Irregular Asynchronous State.Frontiers in neural circuits · 2021Article
- Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex.PLoS computational biology · 2020Article
- Article
- Degeneracy in hippocampal physiology and plasticity.Hippocampus · 2019Review
- Postsynaptic Stability and Variability Described by a Stochastic Model of Endosomal Trafficking.Frontiers in cellular neuroscience · 2019Article
- Article
- Computational Models for Calcium-Mediated Astrocyte Functions.Frontiers in computational neuroscience · 2018Review
- Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures.Frontiers in neuroinformatics · 2018Article
- FindSim: A Framework for Integrating Neuronal Data and Signaling Models.Frontiers in neuroinformatics · 2018Article
- Reproducibility and Comparability of Computational Models for Astrocyte Calcium Excitability.Frontiers in neuroinformatics · 2017Article
- A Computational Model for the AMPA Receptor Phosphorylation Master Switch Regulating Cerebellar Long-Term Depression.PLoS computational biology · 2016Article
- A Cognitive Model Based on Neuromodulated Plasticity.Computational intelligence and neuroscience · 2016Article
- Pancreatic Beta Cell G-Protein Coupled Receptors and Second Messenger Interactions: A Systems Biology Computational Analysis.PloS one · 2016Article
- Shaping synaptic learning by the duration of postsynaptic action potential in a new STDP model.PloS one · 2014Article
- Heterosynaptic plasticity prevents runaway synaptic dynamics.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2013Article
- The delicate bistability of CaMKII.Biophysical journal · 2013Article
- Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.PloS one · 2013Article
- CaMKII activation and dynamics are independent of the holoenzyme structure: an infinite subunit holoenzyme approximation.Physical biology · 2012Article
- Modeling signal transduction leading to synaptic plasticity: evaluation and comparison of five models.EURASIP journal on bioinformatics & systems biology · 2011Article
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Authors and funding
5 authors.
Funding
Abstract
More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.
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