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| Format: | Preprint |
| Published: |
2025
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| Online Access: | https://arxiv.org/abs/2504.10401 |
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| _version_ | 1866908318539186176 |
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| author | Vidybida, A. K. |
| author_facet | Vidybida, A. K. |
| contents | It has been discovered before (arXiv:2306.07676) that for the selectivity gain due to fluctuations in the process of primary odor reception by olfactory receptor neuron (ORN) there exists an optimal concentration of odors at which increased selectivity is mostly manifested. We estimate by means of numerical simulation what could be the gain value at that concentration by modeling ORN as a leaky integrate-and-fire neuron with membrane populated by receptor proteins R which bind and release odor molecules randomly. Each R is modeled as a ligand-gated ion channel, and binding-releasing is modeled as a Markov stochastic process. Possible values for the selectivity gain are calculated for ORN parameters suggested by experimental data.
Keywords: ORN, selectivity, receptor proteins, fluctuations, stochastic process, Markov process |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10401 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Selectivity gain in olfactory receptor neuron at optimal odor concentration Vidybida, A. K. Neurons and Cognition It has been discovered before (arXiv:2306.07676) that for the selectivity gain due to fluctuations in the process of primary odor reception by olfactory receptor neuron (ORN) there exists an optimal concentration of odors at which increased selectivity is mostly manifested. We estimate by means of numerical simulation what could be the gain value at that concentration by modeling ORN as a leaky integrate-and-fire neuron with membrane populated by receptor proteins R which bind and release odor molecules randomly. Each R is modeled as a ligand-gated ion channel, and binding-releasing is modeled as a Markov stochastic process. Possible values for the selectivity gain are calculated for ORN parameters suggested by experimental data. Keywords: ORN, selectivity, receptor proteins, fluctuations, stochastic process, Markov process |
| title | Selectivity gain in olfactory receptor neuron at optimal odor concentration |
| topic | Neurons and Cognition |
| url | https://arxiv.org/abs/2504.10401 |