Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

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dc.contributor	Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada I
dc.contributor	Universitat Politècnica de Catalunya. EGSA - Equacions Diferencials, Geometria, Sistemes Dinàmics i de Control, i Aplicacions
dc.contributor.author	Benita, Jose M.
dc.contributor.author	Guillamon Grabolosa, Antoni
dc.contributor.author	Deco, Gustavo
dc.contributor.author	Sánchez-Vives, Maria V.
dc.date	2012-08-28
dc.identifier.citation	Benita, J. [et al.]. Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex. "Frontiers in Computational Neuroscience", 28 Agost 2012, vol. 6, núm. 64, p. 1-17.
dc.identifier.citation	1662-5188
dc.identifier.citation	10.3389/fncom.2012.00064
dc.identifier.citation	22973221
dc.identifier.uri	http://hdl.handle.net/2117/16721
dc.language.iso	eng
dc.relation	http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428579/
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject	Cerebral cortex
dc.subject	Computational neuroscience
dc.subject	cortical activity
dc.subject	network model
dc.subject	short-term depression
dc.subject	up/down state
dc.subject	synaptic plasticity
dc.subject	Escorça cerebral
dc.subject	Neurociència computacional
dc.title	Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/article
dc.description.abstract	Short-termsynapticdepression(STD)isaformofsynapticplasticitythathasalargeimpactonnetworkcomputations.ExperimentalresultssuggestthatSTDismodulatedbycorticalactivity,decreasingwithactivityinthenetworkandincreasingduringsilentstates.Here,weexploreddifferentactivity-modulationprotocolsinabiophysicalnetworkmodelforwhichthemodeldisplayedlessSTDwhenthenetworkwasactivethanwhenitwassilent,inagreementwithexperimentalresults.Furthermore,westudiedhowtrainsofsynapticpotentialshadlesserdecayduringperiodsofactivity(UPstates)thanduringsilentperiods(DOWNstates),providingnewexperimentalpredictions.WenexttackledtheinversequestionofwhatistheimpactofmodifyingSTDparametersontheemergentactivityofthenetwork,aquestiondifficulttoanswerexperimentally.Wefoundthatsynapticdepressionofcorticalconnectionshadacriticalroletodeterminetheregimeofrhythmiccorticalactivity.WhilelowSTDresultedinanemergentrhythmicactivitywithshortUPstatesandlongDOWNstates,increasingSTDresultedinlongerandmorefrequentUPstatesinterleavedwithshortsilentperiods.Astillhighersynapticdepressionsetthenetworkintoanon-oscillatoryfiringregimewhereDOWNstatesnolongeroccurred.ThespeedofpropagationofUPstatesalongthenetworkwasnotfoundtobemodulatedbySTDduringtheoscillatoryregime;itremainedrelativelystableoverarangeofvaluesofSTD.Overall,wefoundthatthemutualinteractionsbetweensynapticdepressionandongoingnetworkactivityarecriticaltodeterminethemechanismsthatmodulatecorticalemergentpatterns
dc.description.abstract	Peer Reviewed

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