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
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Czech description
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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
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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
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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