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dc.contributor.authorGlackin, Cornelius
dc.contributor.authorMaguire, Liam
dc.contributor.authorMcDaid, Liam
dc.contributor.authorWade, John
dc.date.accessioned2013-01-14T15:29:10Z
dc.date.available2013-01-14T15:29:10Z
dc.date.issued2012
dc.identifier.citationGlackin , C , Maguire , L , McDaid , L & Wade , J 2012 , ' Synchrony : A spiking-based mechanism for processing sensory stimuli ' , Neural Networks , vol. 32 , pp. 26-34 . https://doi.org/10.1016/j.neunet.2012.02.020
dc.identifier.issn1879-2782
dc.identifier.urihttp://hdl.handle.net/2299/9624
dc.descriptionCopyright © 2012 Elsevier Ltd. All rights reserved.
dc.description.abstractSynchronous behaviour of neurons is both beneficial and detrimental to the neural code. On the one extreme, synchronous firing activity is well known to be a symptom of epileptic seizures, whilst on the other synchrony provides a mechanism for coordinating brain activity. This paper briefly reviews some current thinking with regard to synchrony, and outlines some experiments with LIF neurons that harness near-synchronous states for processing biologically-realistic sensory stimuli. Inspired by the topology of neurons in the cochlear nucleus, laterally connected leaky integrate and fire neurons, operating in near-synchronous states, are investigated for their ability to reduce noisy spikes and increase spectral contrast of auditory stimuli. Two connectivity parameters, referred to as connection length and neighbourhood radius, are introduced to configure lateral inhibitory connectivity to generate this neural behaviour. Information-theoretic principles are then employed to quantify the information retained by the coding, and then this is compared to the information retained by the various output topologies.en
dc.format.extent591084
dc.language.isoeng
dc.relation.ispartofNeural Networks
dc.titleSynchrony : A spiking-based mechanism for processing sensory stimulien
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.1016/j.neunet.2012.02.020
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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