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A Theoretical Framework to Derive Simple, Firing-Rate-Dependent Mathematical Models of Synaptic Plasticity

dc.contributor.authorLappalainen, Janne
dc.contributor.authorHerpich, Juliane
dc.contributor.authorTetzlaff, Christian
dc.date.accessioned2019-05-08T10:46:50Z
dc.date.available2019-05-08T10:46:50Z
dc.date.issued2019de
dc.identifier.urihttp://resolver.sub.uni-goettingen.de/purl?gs-1/16096
dc.description.abstractSynaptic plasticity serves as an essential mechanism underlying cognitive processes as learning and memory. For a better understanding detailed theoretical models combine experimental underpinnings of synaptic plasticity and match experimental results. However, these models are mathematically complex impeding the comprehensive investigation of their link to cognitive processes generally executed on the neuronal network level. Here, we derive a mathematical framework enabling the simplification of such detailed models of synaptic plasticity facilitating further mathematical analyses. By this framework we obtain a compact, firing-rate-dependent mathematical formulation, which includes the essential dynamics of the detailed model and, thus, of experimentally verified properties of synaptic plasticity. Amongst others, by testing our framework by abstracting the dynamics of two well-established calcium-dependent synaptic plasticity models, we derived that the synaptic changes depend on the square of the presynaptic firing rate, which is in contrast to previous assumptions. Thus, the here-presented framework enables the derivation of biologically plausible but simple mathematical models of synaptic plasticity allowing to analyze the underlying dependencies of synaptic dynamics from neuronal properties such as the firing rate and to investigate their implications in complex neuronal networks.de
dc.description.sponsorshipOpen-Access-Publikationsfonds 2019
dc.language.isoengde
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/732266/EU//Plan4Actde
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSTDP; synaptic plasticity; calcium; regression analysis; learning; activity-dependencyde
dc.subject.ddc530
dc.titleA Theoretical Framework to Derive Simple, Firing-Rate-Dependent Mathematical Models of Synaptic Plasticityde
dc.typejournalArticlede
dc.identifier.doi10.3389/fncom.2019.00026
dc.identifier.doi10.3389/fncom.2019.00026.s001
dc.type.versionpublishedVersionde
dc.relation.eISSN1662-5188
dc.bibliographicCitation.volume13de
dc.type.subtypejournalArticle
dc.bibliographicCitation.articlenumber26de
dc.description.statuspeerReviewedde
dc.bibliographicCitation.journalFrontiers in Computational Neurosciencede


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