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dc.contributor.authorSchmuker, Michael
dc.contributor.authorKupper, Rüdiger
dc.contributor.authorAertsen, Ad
dc.contributor.authorWachtler, Thomas
dc.contributor.authorGewaltig, Marc-Oliver
dc.date.accessioned2021-05-11T23:09:13Z
dc.date.available2021-05-11T23:09:13Z
dc.date.issued2021-04-01
dc.identifier.citationSchmuker , M , Kupper , R , Aertsen , A , Wachtler , T & Gewaltig , M-O 2021 , ' Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code. ' , Biological Cybernetics , vol. 115 , no. 2 , pp. 161-176 . https://doi.org/10.1007/s00422-021-00866-w
dc.identifier.issn0340-1200
dc.identifier.otherPURE: 24542351
dc.identifier.otherPURE UUID: ce59dd03-9c73-49bc-b37a-d31347a10981
dc.identifier.otherScopus: 85103423986
dc.identifier.urihttp://hdl.handle.net/2299/24478
dc.descriptionReplaces preprint with RIS ID 16546182, "How the visual system can detect feature homogeneity from spike latencies".
dc.description.abstractIn studies of the visual system as well as in computer vision, the focus is often on contrast edges. However, the primate visual system contains a large number of cells that are insensitive to spatial contrast and, instead, respond to uniform homogeneous illumination of their visual field. The purpose of this information remains unclear. Here, we propose a mechanism that detects feature homogeneity in visual areas, based on latency coding and spike time coincidence, in a purely feed-forward and therefore rapid manner. We demonstrate how homogeneity information can interact with information on contrast edges to potentially support rapid image segmentation. Furthermore, we analyze how neuronal crosstalk (noise) affects the mechanism's performance. We show that the detrimental effects of crosstalk can be partly mitigated through delayed feed-forward inhibition that shapes bi-phasic post-synaptic events. The delay of the feed-forward inhibition allows effectively controlling the size of the temporal integration window and, thereby, the coincidence threshold. The proposed model is based on single-spike latency codes in a purely feed-forward architecture that supports low-latency processing, making it an attractive scheme of computation in spiking neuronal networks where rapid responses and low spike counts are desired.en
dc.language.isoeng
dc.relation.ispartofBiological Cybernetics
dc.rightsEmbargoed
dc.titleFeed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code.en
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.description.statusPeer reviewed
dc.date.embargoedUntil2022-03-31
dc.relation.schoolSchool of Physics, Engineering & Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2021-04-01
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1007/s00422-021-00866-w
rioxxterms.licenseref.uriUnspecified
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeEmbargoed


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