Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/135297
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dc.contributor.authorBreskin, Ilan-
dc.contributor.authorSoriano i Fradera, Jordi-
dc.contributor.authorMoses, Elisha-
dc.contributor.authorTlusty, Tsvi-
dc.date.accessioned2019-06-18T11:41:49Z-
dc.date.available2019-06-18T11:41:49Z-
dc.date.issued2006-10-30-
dc.identifier.issn0031-9007-
dc.identifier.urihttp://hdl.handle.net/2445/135297-
dc.description.abstractWe study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a graph-theoretic approach to show that the connectivity undergoes a percolation transition. This occurs as the giant component disintegrates, characterized by a power law with an exponent β ≃ 0.65 . β is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is Gaussian rather than scale free.-
dc.format.extent4 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherAmerican Physical Society-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1103/PhysRevLett.97.188102-
dc.relation.ispartofPhysical Review Letters, 2006, vol. 97, num. 18, p. 188102-
dc.relation.urihttps://doi.org/10.1103/PhysRevLett.97.188102-
dc.rights(c) American Physical Society, 2006-
dc.sourceArticles publicats en revistes (Física de la Matèria Condensada)-
dc.subject.classificationFísica de partícules-
dc.subject.classificationExperiments-
dc.subject.otherParticle physics-
dc.subject.otherExperiments-
dc.titlePercolation in Living Neural Networks-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec601147-
dc.date.updated2019-06-18T11:41:49Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Articles publicats en revistes (Física de la Matèria Condensada)

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