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Collective Spiking Dynamics in Cortical Networks

dc.contributor.advisorPriesemann, Viola Dr.
dc.contributor.authorWilting, Jens
dc.date.accessioned2020-10-14T10:22:24Z
dc.date.available2020-10-14T10:22:24Z
dc.date.issued2020-10-14
dc.identifier.urihttp://hdl.handle.net/21.11130/00-1735-0000-0005-14B2-B
dc.identifier.urihttp://dx.doi.org/10.53846/goediss-8254
dc.language.isoengde
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc530de
dc.titleCollective Spiking Dynamics in Cortical Networksde
dc.typedoctoralThesisde
dc.contributor.refereePriesemann, Viola Dr.
dc.date.examination2020-09-24
dc.subject.gokPhysik (PPN621336750)de
dc.description.abstractengEven though information processing in the cortex most likely emerges from the collective interplay of billions of neurons, even basic properties of collective dynamics in cortical networks are still not known with certainty. In this dissertation, which is a collection of four published articles, we argue that this is likely because their assessment is hampered by spatial subsampling, i.e., the limitation that only a tiny fraction of all neurons can be recorded simultaneously with millisecond precision. We derive an estimator that allows to classify spreading dynamics even under strong subsampling. Building on this estimator, we identify that consistently for rat, cat, and monkey cortex operates in a "reverberating" regime, which allows input to reverberate in the network for hundreds of milliseconds. We present a framework how cortical networks can self-organize to this reverberating regime, or to input-driven and bursting states depending on the input to the network. Finally, we discuss how the reverberating regime can form the substrate for adaptive computation.de
dc.contributor.coRefereeWörgötter, Florentin Prof. Dr.
dc.contributor.thirdRefereeScherberger, Hansjörg Prof. Dr.
dc.contributor.thirdRefereeGeisel, Theo Prof. Dr.
dc.contributor.thirdRefereeKlumpp, Stefan Prof. Dr.
dc.contributor.thirdRefereeSollich, Peter Prof. Dr.
dc.subject.engpropagationde
dc.subject.engcollective dynamicsde
dc.subject.engneuronal networksde
dc.subject.engcortexde
dc.subject.engcriticalityde
dc.subject.engreverberationde
dc.subject.engsubsamplingde
dc.subject.engself-organizationde
dc.subject.enghomeostatic plasticityde
dc.identifier.urnurn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-14B2-B-9
dc.affiliation.instituteFakultät für Physikde
dc.identifier.ppn1735627615


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