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dc.contributor.authorSinha, Ankur
dc.contributor.authorMetzner, Christoph
dc.contributor.authorDavey, Neil
dc.contributor.authorAdams, Roderick
dc.contributor.authorSchmuker, Michael
dc.contributor.authorSteuber, Volker
dc.date.accessioned2021-06-14T15:45:01Z
dc.date.available2021-06-14T15:45:01Z
dc.date.issued2021-06-01
dc.identifier.citationSinha , A , Metzner , C , Davey , N , Adams , R , Schmuker , M & Steuber , V 2021 , ' Growth Rules for the Repair of Asynchronous Irregular Neuronal Networks after Peripheral Lesions ' , PLoS Computational Biology , vol. 17 , no. 6 , e1008996 . https://doi.org/10.1371/journal.pcbi.1008996
dc.identifier.issn1553-734X
dc.identifier.urihttp://hdl.handle.net/2299/24581
dc.description© 2021 Sinha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License. https://creativecommons.org/licenses/by/4.0/
dc.description.abstractSeveral homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model of peripheral lesioning and accurately reproduced the characteristics of network repair after deafferentation that are reported in experiments to study the activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed structural plasticity growth rules and the inhibitory synaptic plasticity mechanism that also balances our AI network both contribute to the restoration of the network to pre-deafferentation stable activity levels.en
dc.format.extent35
dc.format.extent5847755
dc.language.isoeng
dc.relation.ispartofPLoS Computational Biology
dc.titleGrowth Rules for the Repair of Asynchronous Irregular Neuronal Networks after Peripheral Lesionsen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionBiocomputation Research Group
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.1371/journal.pcbi.1008996
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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