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000873622 037__ $$aFZJ-2020-00865
000873622 1001_ $$0P:(DE-Juel1)174497$$aLayer, Moritz$$b0$$eCorresponding author$$ufzj
000873622 1112_ $$aDPG Spring Meetings 2019$$cRegensburg$$d2019-03-31 - 2019-04-05$$wGermany
000873622 245__ $$aFocus Session: Collective Dynamics in Neural Networks; Long-Range Collective Dynamics in the Balanced State
000873622 260__ $$c2019
000873622 3367_ $$033$$2EndNote$$aConference Paper
000873622 3367_ $$2DataCite$$aOther
000873622 3367_ $$2BibTeX$$aINPROCEEDINGS
000873622 3367_ $$2DRIVER$$aconferenceObject
000873622 3367_ $$2ORCID$$aLECTURE_SPEECH
000873622 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1580906335_15994$$xOther
000873622 520__ $$aExperimental findings suggest, that cortical networks operate in a balanced state, in which strong recurrent inhibition suppresses single cell input correlations. The balanced state, however, only restricts the average correlations in the network, the distribution of correlations between individual inputs is not constrained. We here investigate this distribution and establish a functional relation between the distance to criticality and the spatial dependence of the statistics of correlations. Therefore, we develop a mean-field theory that goes beyond self-averaging quantities by taking advantage of the symmetry of the disorder-averaged effective connectivity matrix. We demonstrate that spatially organized, balanced networks can show rich pairwise correlation structures, extending far beyond the range of direct connections. Strikingly, the range of these correlations depends on the distance of the network dynamics to a critical point. This relation between the operational regime of the network and the range of correlations is a potential dynamical mechanism that controls the spatial range on which neurons cooperatively perform computations. In the future we will compare our results with data from multi channel recordings to infer new constraints on realistic network models.
000873622 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000873622 536__ $$0G:(GEPRIS)368482240$$aGRK 2416 - GRK 2416: MultiSenses-MultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration (368482240)$$c368482240$$x1
000873622 536__ $$0G:(DE-Juel1)HGF-SMHB-2014-2018$$aMSNN - Theory of multi-scale neuronal networks (HGF-SMHB-2014-2018)$$cHGF-SMHB-2014-2018$$fMSNN$$x2
000873622 536__ $$0G:(EU-Grant)90251$$aSmartstart - SMARTSTART Training Program in Computational Neuroscience (90251)$$c90251$$x3
000873622 7001_ $$0P:(DE-Juel1)156459$$aDahmen, David$$b1$$ufzj
000873622 7001_ $$0P:(DE-Juel1)168574$$aDeutz, Lukas$$b2
000873622 7001_ $$0P:(DE-Juel1)171408$$aDabrowska, Paulina$$b3$$ufzj
000873622 7001_ $$0P:(DE-Juel1)168479$$aVoges, Nicole$$b4$$ufzj
000873622 7001_ $$0P:(DE-Juel1)144168$$aGrün, Sonja$$b5$$ufzj
000873622 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, Markus$$b6$$ufzj
000873622 7001_ $$0P:(DE-Juel1)144806$$aHelias, Moritz$$b7$$ufzj
000873622 7001_ $$0P:(DE-HGF)0$$aPapen, Michael von$$b8
000873622 909CO $$ooai:juser.fz-juelich.de:873622$$pec_fundedresources$$pVDB$$popenaire
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)174497$$aForschungszentrum Jülich$$b0$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)156459$$aForschungszentrum Jülich$$b1$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)171408$$aForschungszentrum Jülich$$b3$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)168479$$aForschungszentrum Jülich$$b4$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144168$$aForschungszentrum Jülich$$b5$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144174$$aForschungszentrum Jülich$$b6$$kFZJ
000873622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144806$$aForschungszentrum Jülich$$b7$$kFZJ
000873622 9131_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0
000873622 9141_ $$y2019
000873622 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000873622 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x1
000873622 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x2
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000873622 980__ $$aI:(DE-Juel1)INM-10-20170113
000873622 980__ $$aI:(DE-Juel1)IAS-6-20130828
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000873622 981__ $$aI:(DE-Juel1)IAS-6-20130828