%0 Journal Article %1 Kotaleski2010Modelling %A Kotaleski, Jeanette H. %A Blackwell, Kim T. %D 2010 %I Nature Publishing Group %J Nature Reviews Neuroscience %K neuroscience %N 4 %P 239--251 %R 10.1038/nrn2807 %T Modelling the molecular mechanisms of synaptic plasticity using systems biology approaches %U http://dx.doi.org/10.1038/nrn2807 %V 11 %X 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.

@article{Kotaleski2010Modelling, abstract = { 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.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Kotaleski, Jeanette H. and Blackwell, Kim T.}, biburl = {https://www.bibsonomy.org/bibtex/25b8e89c68aba46fc8370588777e6f55a/karthikraman}, citeulike-article-id = {6878816}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nrn2807}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nrn2807}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/20300102}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=20300102}, day = 01, doi = {10.1038/nrn2807}, interhash = {0fe06b123b0cb8faccaf1329cd407659}, intrahash = {5b8e89c68aba46fc8370588777e6f55a}, issn = {1471-003X}, journal = {Nature Reviews Neuroscience}, keywords = {neuroscience}, month = apr, number = 4, pages = {239--251}, pmid = {20300102}, posted-at = {2010-03-20 16:37:26}, priority = {2}, publisher = {Nature Publishing Group}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Modelling the molecular mechanisms of synaptic plasticity using systems biology approaches}, url = {http://dx.doi.org/10.1038/nrn2807}, volume = 11, year = 2010 }