Statistical approach in search for optimal signal in simple olfactory neuronal models
| Autor: | Petr Lánský, Ondřej Pokora |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Statistics and Probability
Models Neurological Sensory system Receptors Odorant Signal Olfactory Receptor Neurons General Biochemistry Genetics and Molecular Biology 03 medical and health sciences symbols.namesake 0302 clinical medicine Econometrics Animals Humans Fisher information 030304 developmental biology Mathematics Stochastic Processes 0303 health sciences Models Statistical General Immunology and Microbiology Stochastic process musculoskeletal neural and ocular physiology Applied Mathematics Detector General Medicine Function (mathematics) Kinetics Odor Modeling and Simulation Odorants symbols General Agricultural and Biological Sciences Biological system Algorithms psychological phenomena and processes 030217 neurology & neurosurgery Signal Transduction Coding (social sciences) |
| Zdroj: | Mathematical Biosciences. 214:100-108 |
| ISSN: | 0025-5564 |
| DOI: | 10.1016/j.mbs.2008.02.010 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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