Journal article
Postsynaptic signal transduction models for long-term potentiation and depression
Frontiers in computational neuroscience, Vol.4, pp.152-152
2010
DOI: 10.3389/fncom.2010.00152
PMCID: PMC3006457
PMID: 21188161
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.
Details
- Title: Subtitle
- Postsynaptic signal transduction models for long-term potentiation and depression
- Creators
- Tiina Manninen - Tampere University of Applied SciencesKatri Hituri - Tampere University of Applied SciencesJeanette Hellgren Kotaleski - Karolinska InstitutetKim T. Blackwell - George Mason UniversityMarja-Leena Linne - Tampere University of Applied Sciences
- Resource Type
- Journal article
- Publication Details
- Frontiers in computational neuroscience, Vol.4, pp.152-152
- DOI
- 10.3389/fncom.2010.00152
- PMID
- 21188161
- PMCID
- PMC3006457
- NLM abbreviation
- Front Comput Neurosci
- ISSN
- 1662-5188
- eISSN
- 1662-5188
- Publisher
- Frontiers Media Sa
- Number of pages
- 29
- Grant note
- Emil Aaltonen Foundation 106030; 124615; 126556; 129657 / Academy of Finland; Research Council of Finland Otto A. Malm Foundation HFSP; Human Frontier Science Program Finnish Foundation for Economic and Technology Sciences - KAUTE (Tiina Manninen) R01 AA16022; R01 AA18060 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Swedish Research Council Parkinson's Foundation Finnish Foundation for Technology Promotion 106030; 124615; 126556 / Academy of Finland (AKA); Research Council of Finland
- Language
- English
- Date published
- 2010
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute
- Record Identifier
- 9984446398302771
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