ArticlePloS one2011
Dynamical modeling of the moth pheromone-sensitive olfactory receptor neuron within its sensillar environment.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 14 citations in OpenAlex.
- Gain control in olfactory receptor neurons and the detection of temporal fluctuations in odor concentration.Frontiers in physiology · 2023Article
- Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.PLoS computational biology · 2021Article
- Beverage and Food Fragrance Biotechnology, Novel Applications, Sensory and Sensor Techniques: An Overview.Foods (Basel, Switzerland) · 2019Review
- Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth.Journal of the Royal Society, Interface · 2019Article
- Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.PLoS computational biology · 2014Article
- Kinetics of olfactory responses might largely depend on the odorant-receptor interaction and the odorant deactivation postulated for flux detectors.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2013Review
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2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
In insects, olfactory receptor neurons (ORNs), surrounded with auxiliary cells and protected by a cuticular wall, form small discrete sensory organs--the sensilla. The moth pheromone-sensitive sensillum is a well studied example of hair-like sensillum that is favorable to both experimental and modeling investigations. The model presented takes into account both the molecular processes of ORNs, i.e. the biochemical reactions and ionic currents giving rise to the receptor potential, and the cellular organization and compartmentalization of the organ represented by an electrical circuit. The number of isopotential compartments needed to describe the long dendrite bearing pheromone receptors was determined. The transduction parameters that must be modified when the number of compartments is increased were identified. This model reproduces the amplitude and time course of the experimentally recorded receptor potential. A first complete version of the model was analyzed in response to pheromone pulses of various strengths. It provided a quantitative description of the spatial and temporal evolution of the pheromone-dependent conductances, currents and potentials along the outer dendrite and served to determine the contribution of the various steps in the cascade to its global sensitivity. A second simplified version of the model, utilizing a single depolarizing conductance and leak conductances for repolarizing the ORN, was derived from the first version. It served to analyze the effects on the sensory properties of varying the electrical parameters and the size of the main sensillum parts. The consequences of the results obtained on the still uncertain mechanisms of olfactory transduction in moth ORNs--involvement or not of G-proteins, role of chloride and potassium currents--are discussed as well as the optimality of the sensillum organization, the dependence of biochemical parameters on the neuron spatial extension and the respective contributions of the biochemical and electrical parameters to the overall neuron response.
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