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dc.contributor.authorWybo, Willem A. M.
dc.contributor.authorStiefel, Klaus M.
dc.contributor.authorTorben-Nielsen, Ben
dc.date.accessioned2016-04-04T13:12:50Z
dc.date.available2016-04-04T13:12:50Z
dc.date.issued2013-12
dc.identifier.citationWybo , W A M , Stiefel , K M & Torben-Nielsen , B 2013 , ' The Green's function formalism as a bridge between single- and multi-compartmental modeling ' , Biological Cybernetics , vol. 107 , no. 6 , pp. 685-94 . https://doi.org/10.1007/s00422-013-0568-0
dc.identifier.issn0340-1200
dc.identifier.otherPURE: 9331028
dc.identifier.otherPURE UUID: 1efb8937-1fc8-4a94-9c19-aa901f967f6f
dc.identifier.otherPubMed: 24037222
dc.identifier.otherScopus: 84890981528
dc.identifier.urihttp://hdl.handle.net/2299/16937
dc.description.abstractNeurons are spatially extended structures that receive and process inputs on their dendrites. It is generally accepted that neuronal computations arise from the active integration of synaptic inputs along a dendrite between the input location and the location of spike generation in the axon initial segment. However, many application such as simulations of brain networks use point-neurons-neurons without a morphological component-as computational units to keep the conceptual complexity and computational costs low. Inevitably, these applications thus omit a fundamental property of neuronal computation. In this work, we present an approach to model an artificial synapse that mimics dendritic processing without the need to explicitly simulate dendritic dynamics. The model synapse employs an analytic solution for the cable equation to compute the neuron's membrane potential following dendritic inputs. Green's function formalism is used to derive the closed version of the cable equation. We show that by using this synapse model, point-neurons can achieve results that were previously limited to the realms of multi-compartmental models. Moreover, a computational advantage is achieved when only a small number of simulated synapses impinge on a morphologically elaborate neuron. Opportunities and limitations are discussed.en
dc.format.extent10
dc.language.isoeng
dc.relation.ispartofBiological Cybernetics
dc.subjectAnimals
dc.subjectComputer Simulation
dc.subjectDendrites
dc.subjectHumans
dc.subjectMembrane Potentials
dc.subjectModels, Neurological
dc.subjectNerve Net
dc.subjectNeurons
dc.subjectSynapses
dc.subjectTime Factors
dc.titleThe Green's function formalism as a bridge between single- and multi-compartmental modelingen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
rioxxterms.versionofrecordhttps://doi.org/10.1007/s00422-013-0568-0
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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