Optimal odor intensity in olfactory neuronal models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F09%3A00039594" target="_blank" >RIV/00216224:14310/09:00039594 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Optimal odor intensity in olfactory neuronal models
Original language description
Signal processing in olfactory systems is initiated by binding of odorant molecules to receptor molecules embedded in the membranes of sensory neurons. An approach, which we use here, is based on stochastic variant ofthe law of mass action as a neuronalmodel. A model experiment is considered, in which a fixed odorant concentration is applied several times and realizations of steady-state characteristics are observed. The response is assumed to be a random variable with some probability density functionbelonging to a parametric family with the signal as a parameter. As a measure how well the signal can be estimated from the response, the Fisher information and its lower bounds are used. Another optimality measures are based on the theory of information, especially conditional and unconditional differential entropy. The study extends our previous results.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LC06024" target="_blank" >LC06024: Jaroslav Hájek Center for Theoretical and Applied Statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů