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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F09%3A00039597%21RIV10-MSM-14310___
rdf:type
n9:Vysledek skos:Concept
dcterms:description
Signal processing in olfactory systems is initiated by binding of odorant molecules to receptor molecules embedded in the membranes of sensory neurons. Three theoretical models and a realistic model for binding and activation of odorant in olfactory sensory neurons have been investigated. The models assume that the response, concentration of activated receptors, is determined by the signal, fixed log-concentration of odorant in perireceptor space. Dependency of the mean response on the signal is realized through the input-output function. How the concentration of activated receptors can code the intensity of odorant is analyzed using statistical properties of the steady-state responses. An approach, we use here, is based on stochastic variant of the law of mass action as a neuronal model. A model experiment is considered, in which a fixed odorant concentration is applied several times and realizations of steady-state characteristics are observed. Signal processing in olfactory systems is initiated by binding of odorant molecules to receptor molecules embedded in the membranes of sensory neurons. Three theoretical models and a realistic model for binding and activation of odorant in olfactory sensory neurons have been investigated. The models assume that the response, concentration of activated receptors, is determined by the signal, fixed log-concentration of odorant in perireceptor space. Dependency of the mean response on the signal is realized through the input-output function. How the concentration of activated receptors can code the intensity of odorant is analyzed using statistical properties of the steady-state responses. An approach, we use here, is based on stochastic variant of the law of mass action as a neuronal model. A model experiment is considered, in which a fixed odorant concentration is applied several times and realizations of steady-state characteristics are observed.
dcterms:title
Optimal odor intensity in simple olfactory neuronal models Optimal odor intensity in simple olfactory neuronal models
skos:prefLabel
Optimal odor intensity in simple olfactory neuronal models Optimal odor intensity in simple olfactory neuronal models
skos:notation
RIV/00216224:14310/09:00039597!RIV10-MSM-14310___
n3:aktivita
n4:P
n3:aktivity
P(LC06024)
n3:dodaniDat
n6:2010
n3:domaciTvurceVysledku
n13:2989387 n13:1350374
n3:druhVysledku
n7:O
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
331878
n3:idVysledku
RIV/00216224:14310/09:00039597
n3:jazykVysledku
n8:eng
n3:klicovaSlova
olfactory neuron; optimal stimulus
n3:klicoveSlovo
n11:optimal%20stimulus n11:olfactory%20neuron
n3:kontrolniKodProRIV
[AFD0011CBAA8]
n3:obor
n15:BA
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n17:LC06024
n3:rokUplatneniVysledku
n6:2009
n3:tvurceVysledku
Lánský, Petr Pokora, Ondřej
n5:organizacniJednotka
14310