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Noise Enhanced Signaling in STDP Driven Spiking-Neuron Network

dc.contributor.authorLobov, S.
dc.contributor.authorZhuravlev, M. O.
dc.contributor.authorMakarov Slizneva, Valeriy
dc.contributor.authorKarantsev, V.B.
dc.date.accessioned2023-06-17T22:12:31Z
dc.date.available2023-06-17T22:12:31Z
dc.date.issued2017
dc.description.abstractPopulation spike signaling is widely observed both in intact brain and neuronal cultures. Experimental evidence suggests that a locally applied electrical stimulus can shape the network architecture and thus the neuronal response. However, there is no clue on how this process can be controlled. Here we study a realistic model of a culture of cortical-like neurons with spike timing dependent plasticity. We show that a stimulus applied at a corner of the culture can rebuild synaptic couplings. Then the network eventually switches from a turbulent-like asynchronous spiking to an ordered population spike signaling mode. The structural analysis shows that the stimulus potentiates centrifugal couplings, which promotes spiking waves traveling outwards the stimulus location. This phenomenon can be catalyzed by noise of an intermediate strength. We predict that matured cultures with high connectivity are more susceptible to reconfiguration and generation of a population spike response than young cultures with low connectivity. We also report on an intermittent synchronization causing switches between two quasi-stable states: generation of time-locked population spikes and turbulent spiking. In the turbulent mode the stimulus excites patches of spiking activity randomly traveling in the network. Such a regime can be implemented through a large scale looping of couplings backwards to the stimulus location. We anticipate that the robust mechanisms of shaping the network architecture discussed here can also be effective in more complex preparations and studies of the relationship between network structure and function.
dc.description.departmentDepto. de Análisis Matemático y Matemática Aplicada
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipThis work was supported by the Russian Science Foundation
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/45320
dc.identifier.doi10.1051/mmnp/201712409
dc.identifier.issn0973-5348
dc.identifier.officialurlhttps://www.mmnp-journal.org/articles/mmnp/abs/2017/04/mmnp2017124p109/mmnp2017124p109.html
dc.identifier.relatedurlhttps://www.mmnp-journal.org/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/18217
dc.issue.number4
dc.journal.titleMathematical Modelling of Natural Phenomena
dc.language.isoeng
dc.page.final124
dc.page.initial109
dc.publisherEDP SCIENCES S A,
dc.relation.projectID15-12-10018.
dc.rights.accessRightsrestricted access
dc.subject.cdu517.9
dc.subject.keywordSpiking neuron network
dc.subject.keywordForced synchronization
dc.subject.keywordSynaptic modula-tion
dc.subject.keywordStochastic resonance
dc.subject.ucmEcuaciones diferenciales
dc.subject.unesco1202.07 Ecuaciones en Diferencias
dc.titleNoise Enhanced Signaling in STDP Driven Spiking-Neuron Network
dc.typejournal article
dc.volume.number12
dspace.entity.typePublication
relation.isAuthorOfPublicationa5728eb3-1e14-4d59-9d6f-d7aa78f88594
relation.isAuthorOfPublication.latestForDiscoverya5728eb3-1e14-4d59-9d6f-d7aa78f88594

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