Priesemann, Viola

[["dc.bibliographiccitation.artnumber","031018"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Physical Review X"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Zierenberg, Johannes"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Priesemann, Viola"],["dc.date.accessioned","2022-03-01T11:47:01Z"],["dc.date.available","2022-03-01T11:47:01Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1103/PhysRevX.8.031018"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103887"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","2160-3308"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Homeostatic Plasticity and External Input Shape Neural Network Dynamics"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","022301"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Physical Review E"],["dc.bibliographiccitation.volume","101"],["dc.contributor.author","Zierenberg, Johannes"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Priesemann, Viola"],["dc.contributor.author","Levina, Anna"],["dc.date.accessioned","2022-03-01T11:46:55Z"],["dc.date.available","2022-03-01T11:46:55Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1103/PhysRevE.101.022301"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103846"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","2470-0053"],["dc.relation.issn","2470-0045"],["dc.rights.uri","https://link.aps.org/licenses/aps-default-license"],["dc.title","Description of spreading dynamics by microscopic network models and macroscopic branching processes can differ due to coalescence"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Physical Review E"],["dc.bibliographiccitation.volume","102"],["dc.contributor.author","de Heuvel, Jorge"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Becker, Moritz"],["dc.contributor.author","Priesemann, Viola"],["dc.contributor.author","Zierenberg, Johannes"],["dc.date.accessioned","2021-04-14T08:31:33Z"],["dc.date.available","2021-04-14T08:31:33Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1103/PhysRevE.102.040301"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83634"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","2470-0053"],["dc.relation.issn","2470-0045"],["dc.title","Characterizing spreading dynamics of subsampled systems with nonstationary external input"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","e1008773"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","PLOS Computational Biology"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Hagemann, Annika"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Samimizad, Bita"],["dc.contributor.author","Mormann, Florian"],["dc.contributor.author","Priesemann, Viola"],["dc.contributor.editor","Taylor, Peter Neal"],["dc.date.accessioned","2022-03-01T11:44:09Z"],["dc.date.available","2022-03-01T11:44:09Z"],["dc.date.issued","2021"],["dc.description.abstract","Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state. In this work, we examine two potential scenarios of seizure generation: (i) epileptic cortical areas might generally operate closer to instability, which would make epilepsy patients generally more susceptible to seizures, or (ii) epileptic cortical areas might drift systematically towards instability before seizure onset. We analyzed single-unit spike recordings from both the epileptogenic (focal) and the nonfocal cortical hemispheres of 20 epilepsy patients. We quantified the distance to instability in the framework of criticality, using a novel estimator, which enables an unbiased inference from a small set of recorded neurons. Surprisingly, we found no evidence for either scenario: Neither did focal areas generally operate closer to instability, nor were seizures preceded by a drift towards instability. In fact, our results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians."],["dc.description.abstract","Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state. In this work, we examine two potential scenarios of seizure generation: (i) epileptic cortical areas might generally operate closer to instability, which would make epilepsy patients generally more susceptible to seizures, or (ii) epileptic cortical areas might drift systematically towards instability before seizure onset. We analyzed single-unit spike recordings from both the epileptogenic (focal) and the nonfocal cortical hemispheres of 20 epilepsy patients. We quantified the distance to instability in the framework of criticality, using a novel estimator, which enables an unbiased inference from a small set of recorded neurons. Surprisingly, we found no evidence for either scenario: Neither did focal areas generally operate closer to instability, nor were seizures preceded by a drift towards instability. In fact, our results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians."],["dc.identifier.doi","10.1371/journal.pcbi.1008773"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/102941"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","1553-7358"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Frontiers in Systems Neuroscience"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Dehning, Jonas"],["dc.contributor.author","Pinheiro Neto, Joao"],["dc.contributor.author","Rudelt, Lucas"],["dc.contributor.author","Wibral, Michael"],["dc.contributor.author","Zierenberg, Johannes"],["dc.contributor.author","Priesemann, Viola"],["dc.date.accessioned","2022-03-01T11:44:23Z"],["dc.date.available","2022-03-01T11:44:23Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.3389/fnsys.2018.00055"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103013"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","1662-5137"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","2325"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Nature Communications"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Wilting, Jens"],["dc.contributor.author","Priesemann, Viola"],["dc.date.accessioned","2022-03-01T11:45:56Z"],["dc.date.available","2022-03-01T11:45:56Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1038/s41467-018-04725-4"],["dc.identifier.pii","4725"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103505"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.eissn","2041-1723"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Inferring collective dynamical states from widely unobserved systems"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]