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dc.contributor.authorDrion, Guillaume
dc.contributor.authorDethier, Julie
dc.contributor.authorFranci, Alessio
dc.contributor.authorSepulchre, Rodolphe
dc.date.accessioned2018-10-10T05:19:05Z
dc.date.available2018-10-10T05:19:05Z
dc.date.issued2018-04
dc.identifier.issn1553-734X
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/283435
dc.description.abstractNeuronal information processing is regulated by fast and localized fluctuations of brain states. Brain states reliably switch between distinct spatiotemporal signatures at a network scale even though they are composed of heterogeneous and variable rhythms at a cellular scale. We investigated the mechanisms of this network control in a conductance-based population model that reliably switches between active and oscillatory mean-fields. Robust control of the mean-field properties relies critically on a switchable negative intrinsic conductance at the cellular level. This conductance endows circuits with a shared cellular positive feedback that can switch population rhythms on and off at a cellular resolution. The switch is largely independent from other intrinsic neuronal properties, network size and synaptic connectivity. It is therefore compatible with the temporal variability and spatial heterogeneity induced by slower regulatory functions such as neuromodulation, synaptic plasticity and homeostasis. Strikingly, the required cellular mechanism is available in all cell types that possess T-type calcium channels but unavailable in computational models that neglect the slow kinetics of their activation.
dc.format.mediumElectronic-eCollection
dc.languageeng
dc.publisherPublic Library of Science (PLoS)
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectBrain
dc.subjectNerve Net
dc.subjectNeurons
dc.subjectAnimals
dc.subjectHumans
dc.subjectCalcium Channels, T-Type
dc.subjectComputational Biology
dc.subjectAction Potentials
dc.subjectNeuronal Plasticity
dc.subjectKinetics
dc.subjectModels, Neurological
dc.subjectComputer Simulation
dc.subjectElectrophysiological Phenomena
dc.subjectNeural Networks, Computer
dc.titleSwitchable slow cellular conductances determine robustness and tunability of network states.
dc.typeArticle
prism.issueIdentifier4
prism.publicationDate2018
prism.publicationNamePLoS Comput Biol
prism.startingPagee1006125
prism.volume14
dc.identifier.doi10.17863/CAM.30802
dcterms.dateAccepted2018-04-06
rioxxterms.versionofrecord10.1371/journal.pcbi.1006125
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-04-23
dc.contributor.orcidSepulchre, Rodolphe [0000-0002-7047-3124]
dc.identifier.eissn1553-7358
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEuropean Research Council (670645)
cam.issuedOnline2018-04-23


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International