Statistical approach in search for optimal signal in simple olfactory neuronal models
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
18400236
DOI
10.1016/j.mbs.2008.02.010
PII: S0025-5564(08)00040-0
Knihovny.cz E-zdroje
- MeSH
- algoritmy MeSH
- čichové buňky fyziologie MeSH
- kinetika MeSH
- lidé MeSH
- modely neurologické * MeSH
- odoranty MeSH
- receptory pachové fyziologie MeSH
- signální transdukce * MeSH
- statistické modely MeSH
- stochastické procesy MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- receptory pachové MeSH
Several models (concentration detectors and a flux detector) for coding of odor intensity in olfactory sensory neurons are investigated. Behavior of the system is described by different stochastic processes of binding the odorant molecules to the receptors and their activation. Characteristics how well the odorant concentration can be estimated from the knowledge of response, the number of activated neurons, are studied. The approach is based on the Fisher information and analogous measures. These measures of optimality are computed and applied to locate the odorant concentration which is most suitable for coding. The results are compared with the classical deterministic approach which judges the optimal odorant concentration via steepness of the input-output function.
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