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Modelling the molecular mechanisms of synaptic plasticity using systems biology approaches
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-0550-0739
2010 (English)In: Nature Reviews Neuroscience, ISSN 1471-003X, E-ISSN 1471-0048, Vol. 11, no 4, 239-251 p.Article, review/survey (Refereed) Published
Abstract [en]

Synaptic plasticity is thought to underlie learning and memory, but the complexity of the interactions between the ion channels, enzymes and genes that are involved in synaptic plasticity impedes a deep understanding of this phenomenon. Computer modelling has been used to investigate the information processing that is performed by the signalling pathways involved in synaptic plasticity in principal neurons of the hippocampus, striatum and cerebellum. In the past few years, new software developments that combine computational neuroscience techniques with systems biology techniques have allowed large-scale, kinetic models of the molecular mechanisms underlying long-term potentiation and long-term depression. We highlight important advancements produced by these quantitative modelling efforts and introduce promising approaches that use advancements in live-cell imaging.

Place, publisher, year, edition, pages
2010. Vol. 11, no 4, 239-251 p.
Keyword [en]
long-term potentiation, cam kinase-ii, timing-dependent plasticity, signal-transduction, dendritic spines, positive feedback, stochastic, simulation, postsynaptic density, proteomic analysis, negative feedback
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-19396DOI: 10.1038/nrn2807ISI: 000276631300009Scopus ID: 2-s2.0-77949798185OAI: oai:DiVA.org:kth-19396DiVA: diva2:337443
Funder
Swedish Research CouncilSwedish e‐Science Research Center
Note
QC 20100525Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2017-12-12Bibliographically approved

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Hällgren Kotaleski, Jeanette

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