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dc.contributor.authorValderhaug, Vibeke Devold
dc.contributor.authorGlomm, Wilhelm
dc.contributor.authorSandru, Eugenia Mariana
dc.contributor.authorYasuda, Masahiro
dc.contributor.authorSandvig, Axel
dc.contributor.authorSandvig, Ioanna
dc.date.accessioned2019-10-24T10:51:43Z
dc.date.available2019-10-24T10:51:43Z
dc.date.created2019-10-23T10:06:04Z
dc.date.issued2019
dc.identifier.citationRoyal Society Open Science. 2019, 6 (10), .nb_NO
dc.identifier.issn2054-5703
dc.identifier.urihttp://hdl.handle.net/11250/2624118
dc.description.abstractIn vitro electrophysiological investigation of neural activity at a network level holds tremendous potential for elucidating underlying features of brain function (and dysfunction). In standard neural network modelling systems, however, the fundamental three-dimensional (3D) character of the brain is a largely disregarded feature. This widely applied neuroscientific strategy affects several aspects of the structure–function relationships of the resulting networks, altering network connectivity and topology, ultimately reducing the translatability of the results obtained. As these model systems increase in popularity, it becomes imperative that they capture, as accurately as possible, fundamental features of neural networks in the brain, such as small-worldness. In this report, we combine in vitro neural cell culture with a biologically compatible scaffolding substrate, surface-grafted polymer particles (PPs), to develop neural networks with 3D topology. Furthermore, we investigate their electrophysiological network activity through the use of 3D multielectrode arrays. The resulting neural network activity shows emergent behaviour consistent with maturing neural networks capable of performing computations, i.e. activity patterns suggestive of both information segregation (desynchronized single spikes and local bursts) and information integration (network spikes). Importantly, we demonstrate that the resulting PP-structured neural networks show both structural and functional features consistent with small-world network topology.nb_NO
dc.language.isoengnb_NO
dc.publisherThe Royal Societynb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleFormation of neural networks with structural and functional features consistent with small-world network topology on surface-grafted polymer particlesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber10nb_NO
dc.source.volume6nb_NO
dc.source.journalRoyal Society Open Sciencenb_NO
dc.source.issue10nb_NO
dc.identifier.doihttps://doi.org/10.1098/rsos.191086
dc.identifier.cristin1739752
dc.description.localcode© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.nb_NO
cristin.unitcode194,65,30,0
cristin.unitnameInstitutt for nevromedisin og bevegelsesvitenskap
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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