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2020-06-24Zeitschriftenartikel DOI: 10.18452/23739
Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system
dc.contributor.authorBostner, Žiga
dc.contributor.authorKnoll, Gregory
dc.contributor.authorLindner, Benjamin
dc.date.accessioned2021-11-30T08:35:29Z
dc.date.available2021-11-30T08:35:29Z
dc.date.issued2020-06-24none
dc.identifier.urihttp://edoc.hu-berlin.de/18452/24398
dc.description.abstractInformation about time-dependent sensory stimuli is encoded in the activity of neural populations; distinct aspects of the stimulus are read out by different types of neurons: while overall information is perceived by integrator cells, so-called coincidence detector cells are driven mainly by the synchronous activity in the population that encodes predominantly high-frequency content of the input signal (high-pass information filtering). Previously, an analytically accessible statistic called the partial synchronous output was introduced as a proxy for the coincidence detector cell’s output in order to approximate its information transmission. In the first part of the current paper, we compare the information filtering properties (specifically, the coherence function) of this proxy to those of a simple coincidence detector neuron. We show that the latter’s coherence function can indeed be well-approximated by the partial synchronous output with a time scale and threshold criterion that are related approximately linearly to the membrane time constant and firing threshold of the coincidence detector cell. In the second part of the paper, we propose an alternative theory for the spectral measures (including the coherence) of the coincidence detector cell that combines linear-response theory for shot-noise driven integrate-and-fire neurons with a novel perturbation ansatz for the spectra of spike-trains driven by colored noise. We demonstrate how the variability of the synaptic weights for connections from the population to the coincidence detector can shape the information transmission of the entire two-stage system.eng
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.subjectInformation codingeng
dc.subjectSynchronizationeng
dc.subjectCoincidence detectioneng
dc.subjectNeural computationeng
dc.subject.ddc570 Biologienone
dc.subject.ddc000 Informatik, Informationswissenschaft, allgemeine Werkenone
dc.titleInformation filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural systemnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/24398-1
dc.identifier.doihttp://dx.doi.org/10.18452/23739
dc.type.versionpublishedVersionnone
local.edoc.pages16none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
dc.description.versionPeer Reviewednone
dc.identifier.eissn1432-0770
dcterms.bibliographicCitation.doi10.1007/s00422-020-00838-6
dcterms.bibliographicCitation.journaltitleBiological cyberneticsnone
dcterms.bibliographicCitation.volume114none
dcterms.bibliographicCitation.issue3none
dcterms.bibliographicCitation.originalpublishernameSpringernone
dcterms.bibliographicCitation.originalpublisherplaceBerlin, Heidelbergnone
dcterms.bibliographicCitation.pagestart403none
dcterms.bibliographicCitation.pageend418none
bua.departmentLebenswissenschaftliche Fakultätnone

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