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Presynaptic Spontaneous Activity Enhances the Accuracy of Latency Coding

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F16%3A00464967" target="_blank" >RIV/67985823:_____/16:00464967 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1162/NECO_a_00880" target="_blank" >http://dx.doi.org/10.1162/NECO_a_00880</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1162/NECO_a_00880" target="_blank" >10.1162/NECO_a_00880</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Presynaptic Spontaneous Activity Enhances the Accuracy of Latency Coding

  • Original language description

    The time to the first spike after stimulus onset typically varies with the stimulation intensity. Experimental evidence suggests that neural systems use such response latency to encode information about the stimulus. We investigate the decoding accuracy of the latency code in relation to the level of noise in the form of presynaptic spontaneous activity. Paradoxically, the optimal performance is achieved at a nonzero level of noise and suprathreshold stimulus intensities. We argue that this phenomenon results from the influence of the spontaneous activity on the stabilization of the membrane potential in the absence of stimulation. The reported decoding accuracy improvement represents a novel manifestation of the noise-aided signal enhancement.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    FH - Neurology, neuro-surgery, nuero-sciences

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Neural Computation

  • ISSN

    0899-7667

  • e-ISSN

  • Volume of the periodical

    28

  • Issue of the periodical within the volume

    10

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    19

  • Pages from-to

    2162-2180

  • UT code for WoS article

    000384452300006

  • EID of the result in the Scopus database

    2-s2.0-84988615474