dc.contributor.author | Valderhaug, Vibeke Devold | |
dc.contributor.author | Glomm, Wilhelm | |
dc.contributor.author | Sandru, Eugenia Mariana | |
dc.contributor.author | Yasuda, Masahiro | |
dc.contributor.author | Sandvig, Axel | |
dc.contributor.author | Sandvig, Ioanna | |
dc.date.accessioned | 2019-10-25T09:13:25Z | |
dc.date.available | 2019-10-25T09:13:25Z | |
dc.date.created | 2019-10-23T10:06:04Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Royal Society Open Science. 2019, 6 (10), . | nb_NO |
dc.identifier.issn | 2054-5703 | |
dc.identifier.uri | http://hdl.handle.net/11250/2624397 | |
dc.description.abstract | In vitroelectrophysiological investigation of neural activity at anetwork level holds tremendous potential for elucidatingunderlying features of brain function (and dysfunction). In standard neural network modelling systems, however, the fundamental three-dimensional (3D) character of the brain isa largely disregarded feature. This widely appliedneuroscientific strategy affects several aspects of the structure–function relationships of the resulting networks, alteringnetwork connectivity and topology, ultimately reducing thetranslatability of the results obtained. As these model systems increase in popularity, it becomes imperative that they capture,as accurately as possible, fundamental features of neuralnetworks in the brain, such as small-worldness. In this report,we combinein vitroneural cell culture with a biologicallycompatible scaffolding substrate, surface-grafted polymerparticles (PPs), to develop neural networks with 3D topology.Furthermore, we investigate their electrophysiological networkactivity through the use of 3D multielectrode arrays. Theresulting neural network activity shows emergent behaviour consistent with maturing neural networks capable of performing computations, i.e. activity patternssuggestive 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-worldnetwork topology. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | The Royal Society Publishing | nb_NO |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.subject | neural networks | nb_NO |
dc.subject | polymer particles | nb_NO |
dc.title | Formation of neural networks with structural and functional features consistent with small-world network topology on surface-grafted polymer particles | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.rights.holder | © 2019 The Authors. Published by the Royal Society under the terms of the CreativeCommons Attribution License http://creativecommons.org/licenses/by/4.0/, which permitsunrestricted use, provided the original author and source are credited | nb_NO |
dc.source.pagenumber | 10 | nb_NO |
dc.source.volume | 6 | nb_NO |
dc.source.journal | Royal Society Open Science | nb_NO |
dc.source.issue | 10 | nb_NO |
dc.identifier.doi | https://doi.org/10.1098/rsos.191086 | |
dc.identifier.cristin | 1739752 | |
cristin.unitcode | 7401,80,1,0 | |
cristin.unitname | Bioteknologi og nanomedisin | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |