000828725 001__ 828725
000828725 005__ 20240313094852.0
000828725 037__ $$aFZJ-2017-02591
000828725 1001_ $$0P:(DE-Juel1)156459$$aDahmen, David$$b0$$eCorresponding author$$ufzj
000828725 1112_ $$aNWG meeting 2017$$cGöttingen$$d2017-03-22 - 2017-03-25$$wGermany
000828725 245__ $$aDistributions of covariances as a window intothe operational regime of neuronal networks
000828725 260__ $$c2017
000828725 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1497363188_20574
000828725 3367_ $$033$$2EndNote$$aConference Paper
000828725 3367_ $$2BibTeX$$aINPROCEEDINGS
000828725 3367_ $$2DRIVER$$aconferenceObject
000828725 3367_ $$2DataCite$$aOutput Types/Conference Abstract
000828725 3367_ $$2ORCID$$aOTHER
000828725 520__ $$aMassively parallel recordings of spiking activity in cortical networks show that spike count covariances vary widely across pairs of neurons [Ecker et al., Science (2010)]. Their low average is well understood [Renart et al., Science (2010), Tetzlaff et al., PLoS CB (2012)], but an explanation for the wide distribution in relation to the static (quenched) disorder of the connectivity in recurrent random networks was so far elusive. Starting from spin-glass techniques [Sompolinsky and Zippelius, Phys. Rev. B (1982)] and a generating function representation for the joint probability distribution of the network activity [Chow and Buice, J. Math. Neurosci. (2015)], we derive a finite-size mean-field theory that reduces a disordered to a highly symmetric network with fluctuating auxiliary fields. The exposed analytical relation between the statistics of connections and the statistics of pairwise covariances shows that both, average and dispersion of the latter, diverge at a critical coupling. At this point, a network of nonlinear units transits from regular to chaotic dynamics. Applying these results to recordings from the mammalian brain suggests its operation close to this edge of criticality.
000828725 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000828725 536__ $$0G:(DE-HGF)POF3-571$$a571 - Connectivity and Activity (POF3-571)$$cPOF3-571$$fPOF III$$x1
000828725 536__ $$0G:(DE-HGF)POF2-331$$a331 - Signalling Pathways and Mechanisms in the Nervous System (POF2-331)$$cPOF2-331$$fPOF II$$x2
000828725 536__ $$0G:(DE-Juel1)HGF-SMHB-2014-2018$$aMSNN - Theory of multi-scale neuronal networks (HGF-SMHB-2014-2018)$$cHGF-SMHB-2014-2018$$fMSNN$$x3
000828725 536__ $$0G:(EU-Grant)720270$$aHBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)$$c720270$$fH2020-Adhoc-2014-20$$x4
000828725 536__ $$0G:(DE-Juel1)HGF-SMHB-2013-2017$$aSMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)$$cHGF-SMHB-2013-2017$$fSMHB$$x5
000828725 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, Markus$$b1$$ufzj
000828725 7001_ $$0P:(DE-Juel1)144806$$aHelias, Moritz$$b2$$ufzj
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000828725 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)156459$$aForschungszentrum Jülich$$b0$$kFZJ
000828725 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144174$$aForschungszentrum Jülich$$b1$$kFZJ
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000828725 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
000828725 9131_ $$0G:(DE-HGF)POF3-571$$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$$vConnectivity and Activity$$x1
000828725 9131_ $$0G:(DE-HGF)POF2-331$$1G:(DE-HGF)POF2-330$$2G:(DE-HGF)POF2-300$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lFunktion und Dysfunktion des Nervensystems$$vSignalling Pathways and Mechanisms in the Nervous System$$x2
000828725 9141_ $$y2017
000828725 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000828725 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x1
000828725 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x2
000828725 980__ $$aabstract
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000828725 980__ $$aI:(DE-Juel1)IAS-6-20130828
000828725 980__ $$aI:(DE-Juel1)INM-10-20170113
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000828725 981__ $$aI:(DE-Juel1)IAS-6-20130828