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dc.contributor.authorTorben-Nielsen, Ben
dc.contributor.authorStiefel, Klaus M.
dc.date.accessioned2016-03-08T11:43:39Z
dc.date.available2016-03-08T11:43:39Z
dc.date.issued2010
dc.identifier.citationTorben-Nielsen , B & Stiefel , K M 2010 , ' Wide-field motion integration in fly VS cells : insights from an inverse approach ' , PLoS Computational Biology , vol. 6 , no. 9 , e1000932 . https://doi.org/10.1371/journal.pcbi.1000932
dc.identifier.issn1553-734X
dc.identifier.otherPURE: 9331194
dc.identifier.otherPURE UUID: f7d3234c-0220-49a8-a3fb-38f71c3e67d2
dc.identifier.otherPubMed: 20957028
dc.identifier.otherScopus: 78049425659
dc.identifier.urihttp://hdl.handle.net/2299/16740
dc.descriptionCopyright: © 2010 Torben-Nielsen, Stiefel. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
dc.description.abstractFly lobula plate tangential cells are known to perform wide-field motion integration. It is assumed that the shape of these neurons, and in particular the shape of the subclass of VS cells, is responsible for this type of computation. We employed an inverse approach to investigate the morphology-function relationship underlying wide-field motion integration in VS cells. In the inverse approach detailed, model neurons are optimized to perform a predefined computation: here, wide-field motion integration. We embedded the model neurons to be optimized in a biologically plausible model of fly motion detection to provide realistic inputs, and subsequently optimized model neuron with and without active conductances (g(Na), g(K), g(K(Na))) along their dendrites to perform this computation. We found that both passive and active optimized model neurons perform well as wide-field motion integrators. In addition, all optimized morphologies share the same blueprint as real VS cells. In addition, we also found a recurring blueprint for the distribution of g(K) and g(Na) in the active models. Moreover, we demonstrate how this morphology and distribution of conductances contribute to wide-field motion integration. As such, by using the inverse approach we can predict the still unknown distribution of g(K) and g(Na) and their role in motion integration in VS cellsen
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofPLoS Computational Biology
dc.rightsOpen
dc.subjectAlgorithms
dc.subjectAnimals
dc.subjectComputational Biology
dc.subjectComputer Simulation
dc.subjectDendrites
dc.subjectDiptera
dc.subjectElectrophysiology
dc.subjectIon Channels
dc.subjectModels, Neurological
dc.subjectMotion
dc.subjectNeurons
dc.subjectVisual Fields
dc.titleWide-field motion integration in fly VS cells : insights from an inverse approachen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
dc.description.versiontypeFinal Published version
dcterms.dateAccepted2010
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1371/journal.pcbi.1000932
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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