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@article{770535,
author = {Pokora, Ondřej and Lánský, Petr},
article_location = {Amsterdam},
article_number = {Issues 1-2},
keywords = {Fisher information; Olfactory neuron; Optimal signal},
language = {eng},
issn = {0025-5564},
journal = {Mathematical Biosciences},
title = {Statistical approach in search for optimal signal in simple olfactory neuronal models},
url = {http://dx.doi.org/10.1016/j.mbs.2008.02.010},
volume = {Volume 214},
year = {2008}
}
TY - JOUR
ID - 770535
AU - Pokora, Ondřej - Lánský, Petr
PY - 2008
TI - Statistical approach in search for optimal signal in simple olfactory neuronal models
JF - Mathematical Biosciences
VL - Volume 214
IS - Issues 1-2
SP - 100
EP - 100
PB - Elsevier
SN - 00255564
KW - Fisher information
KW - Olfactory neuron
KW - Optimal signal
UR - http://dx.doi.org/10.1016/j.mbs.2008.02.010
N2 - 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.
ER -
POKORA, Ondřej a Petr LÁNSKÝ. Statistical approach in search for optimal signal in simple olfactory neuronal models. \textit{Mathematical Biosciences}. Amsterdam: Elsevier, Volume 214, Issues 1-2, s.~100-108. ISSN~0025-5564. 2008.
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