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dc.contributor.authorSteuber, Volker
dc.contributor.authorWillshaw, D.
dc.contributor.authorvan Ooyen, A.
dc.date.accessioned2008-05-20T08:38:04Z
dc.date.available2008-05-20T08:38:04Z
dc.date.issued2006
dc.identifier.citationSteuber , V , Willshaw , D & van Ooyen , A 2006 , ' Generation of time delays: simplified models of intracellular signalling in cerebellar Purkinje cells ' , Network: Computation in Neural Systems , vol. 17 , no. 2 , pp. 173-191 .
dc.identifier.issn0954-898X
dc.identifier.otherdspace: 2299/2026
dc.identifier.urihttp://hdl.handle.net/2299/2026
dc.description.abstractIn many neuronal systems, information is encoded in temporal spike patterns. The recognition and storage of temporal patterns requires the generation and modulation of time delays between inputs and outputs. In cerebellar Purkinje cells, stimulation of metabotropic glutamate receptors (mGluRs) results in a delayed calcium and voltage response that has been implicated in classical conditioning and temporal pattern recognition. Here, we analyse and simplify a complex model of the intracellular signalling network that has been proposed as a substrate for this delayed response. We systematically simplify the original model, present a minimal model of time delay generation, and show that a delayed response can be produced by the combination of negative feedback and autocatalysis, without any intervening signalling steps that would contribute additive delays. The minimal model is analysed using phase plane methods, and classied as an excitable system. We discuss the implication of excitability for computations performed by intracellular signalling networks in generalen
dc.format.extent254369
dc.language.isoeng
dc.relation.ispartofNetwork: Computation in Neural Systems
dc.titleGeneration of time delays: simplified models of intracellular signalling in cerebellar Purkinje cellsen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionCentre for Future Societies Research
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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