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1、Science.Authormanuscript;availableinPMCMay1,2014.PMCID:PMC3905047Publishedinfinaleditedformas:NIHMSID:NIHMS548001Science.Nov1,2013;342(6158):1238406.doi:10.1126/science.1238406CorticalHighDensityCounterstreamArchitectures1,2,345#1,2#6,7,†NikolaT.Markov
2、,MáriaErcseyRavasz,DavidC.VanEssen,KennethKnoblauch,ZoltánToroczkai,andHenry#1,2,†Kennedy1StemcellandBrainResearchInstitute,INSERMU846,18AvenueDoyenLépine,69500Bron,France2UniversitédeLyon,UniversitéLyonI,69003Lyon,France3YaleUniversity,DepartmentofNeu
3、robiology,NewHaven,CT06520,USA4FacultyofPhysics,BabeşBolyaiUniversity,ClujNapoca,400084Romania5DepartmentofAnatomyandNeurobiology,WashingtonUniversitySchoolofMedicine,St.Louis,MO631101093,USA6DepartmentofPhysicsandInterdisciplinaryCenterforNetworkScien
4、ceandApplications,UniversityofNotreDame,NotreDame,IN46556,USA7MaxPlanckInstituteforthePhysicsofComplexSystems,01187Dresden,Germany#Contributedequally.†Correspondingauthor.Email:henry.kennedy@inserm.fr(H.K.);Email:toro@nd.edu(Z.T.)CopyrightnoticeandDisc
5、laimerThepublisher'sfinaleditedversionofthisarticleisavailableatScienceSeeotherarticlesinPMCthatcitethepublishedarticle.AbstractGoto:Smallworldnetworksprovideanappealingdescriptionofcorticalarchitectureowingtotheircapacityforintegrationandsegregationco
6、mbinedwithaneconomyofconnectivity.Previousreportsoflowdensityinterarealgraphsandapparentsmallworldpropertiesarechallengedbydatathatrevealhighdensitycorticalgraphsinwhicheconomyofconnectionsisachievedbyweightheterogeneityanddistanceweightcorrelations.Th
7、esepropertiesdefineamodelthatpredictsmanybinaryandweightedfeaturesofthecorticalnetworkincludingacoreperiphery,atypicalfeatureofselforganizinginformationprocessingsystems.Feedbackandfeedforwardpathwaysbetweenareasexhibitadualcounterstreamorganization,an
8、dtheirintegrationintolocalcircuitsconstrainscorticalcomputation.Here,weproposeabowtierepresentationofinterarealarchitecturederivedfromthehierarchicallaminarweightsofpathwaysbetweenthehighefficiencydensecoreandperiphery.Becausetheconcept
