Postsynaptic signal transduction models for long-term potentiation and depression

More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation and depression. 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 (long-term potentiation or long-term depression) 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 method). 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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Tiina Manninen [verfasserIn] Katri Hituri [verfasserIn] Jeanette eHellgren Kotaleski [verfasserIn] Kim T. Blackwell [verfasserIn] Marja-Leena Linne [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Long-Term Potentiation computational model plasticity Long-term depression kinetic model postsynaptic signal transduction model

Übergeordnetes Werk:	In: Frontiers in Computational Neuroscience - Frontiers Media S.A., 2008, 4(2010)
Übergeordnetes Werk:	volume:4 ; year:2010

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fncom.2010.00152

Katalog-ID:	DOAJ009205403

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authorswithroles_txt_mv	Tiina Manninen @@aut@@ Katri Hituri @@aut@@ Jeanette eHellgren Kotaleski @@aut@@ Kim T. Blackwell @@aut@@ Marja-Leena Linne @@aut@@
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callnumber-first	R - Medicine
author	Tiina Manninen
spellingShingle	Tiina Manninen misc RC321-571 misc Long-Term Potentiation misc computational model misc plasticity misc Long-term depression misc kinetic model misc postsynaptic signal transduction model misc Neurosciences. Biological psychiatry. Neuropsychiatry Postsynaptic signal transduction models for long-term potentiation and depression
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topic_title	RC321-571 Postsynaptic signal transduction models for long-term potentiation and depression Long-Term Potentiation computational model plasticity Long-term depression kinetic model postsynaptic signal transduction model
topic	misc RC321-571 misc Long-Term Potentiation misc computational model misc plasticity misc Long-term depression misc kinetic model misc postsynaptic signal transduction model misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_unstemmed	misc RC321-571 misc Long-Term Potentiation misc computational model misc plasticity misc Long-term depression misc kinetic model misc postsynaptic signal transduction model misc Neurosciences. Biological psychiatry. Neuropsychiatry
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title	Postsynaptic signal transduction models for long-term potentiation and depression
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title_sort	postsynaptic signal transduction models for long-term potentiation and depression
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title_auth	Postsynaptic signal transduction models for long-term potentiation and depression
abstract	More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation and depression. 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 (long-term potentiation or long-term depression) 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 method). 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.
abstractGer	More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation and depression. 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 (long-term potentiation or long-term depression) 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 method). 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.
abstract_unstemmed	More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation and depression. 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 (long-term potentiation or long-term depression) 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 method). 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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title_short	Postsynaptic signal transduction models for long-term potentiation and depression
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