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2021-05-18Zeitschriftenartikel DOI: 10.18452/26605
Recurrence-mediated suprathreshold stochastic resonance
dc.contributor.authorKnoll, Gregory
dc.contributor.authorLindner, Benjamin
dc.date.accessioned2023-05-25T12:19:58Z
dc.date.available2023-05-25T12:19:58Z
dc.date.issued2021-05-18none
dc.date.updated2023-03-25T17:39:25Z
dc.identifier.issn0929-5313
dc.identifier.urihttp://edoc.hu-berlin.de/18452/27305
dc.description.abstractIt has previously been shown that the encoding of time-dependent signals by feedforward networks (FFNs) of processing units exhibits suprathreshold stochastic resonance (SSR), which is an optimal signal transmission for a finite level of independent, individual stochasticity in the single units. In this study, a recurrent spiking network is simulated to demonstrate that SSR can be also caused by network noise in place of intrinsic noise. The level of autonomously generated fluctuations in the network can be controlled by the strength of synapses, and hence the coding fraction (our measure of information transmission) exhibits a maximum as a function of the synaptic coupling strength. The presence of a coding peak at an optimal coupling strength is robust over a wide range of individual, network, and signal parameters, although the optimal strength and peak magnitude depend on the parameter being varied. We also perform control experiments with an FFN illustrating that the optimized coding fraction is due to the change in noise level and not from other effects entailed when changing the coupling strength. These results also indicate that the non-white (temporally correlated) network noise in general provides an extra boost to encoding performance compared to the FFN driven by intrinsic white noise fluctuations.eng
dc.description.sponsorshipDeutsche Forschungsgemeinschaft
dc.description.sponsorshipHumboldt-Universität zu Berlin (1034)
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSuprathreshold stochastic resonanceeng
dc.subjectRecurrenceeng
dc.subjectSpiking networkseng
dc.subjectSignal encodingeng
dc.subject.ddc530 Physiknone
dc.titleRecurrence-mediated suprathreshold stochastic resonancenone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/27305-5
dc.identifier.doihttp://dx.doi.org/10.18452/26605
dc.type.versionpublishedVersionnone
local.edoc.pages12none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
dc.description.versionPeer Reviewednone
dc.identifier.eissn1573-6873
dcterms.bibliographicCitation.doi10.1007/s10827-021-00788-3none
dcterms.bibliographicCitation.journaltitleJournal of computational neurosciencenone
dcterms.bibliographicCitation.volume49none
dcterms.bibliographicCitation.issue4none
dcterms.bibliographicCitation.originalpublishernameSpringernone
dcterms.bibliographicCitation.originalpublisherplaceNew York, NYnone
dcterms.bibliographicCitation.pagestart407none
dcterms.bibliographicCitation.pageend418none
bua.departmentMathematisch-Naturwissenschaftliche Fakultätnone

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