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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…

神经元与认知 · 定量生物学 2025-04-15 A. K. Vidybida

Selectivity of olfactory receptor neuron (ORN) is compared with that of its receptor proteins (R) with fluctuations of odor binding-releasing process taken into account. The binding-releasing process is modeled as N Bernoulli trials, where…

生物物理 · 物理学 2022-07-20 A. Vidybida

It was observed before that due to convergence in the olfactory system a possible amplification can be as large as the degree of convergence. This is in the case when a single impulse from the converging inputs is enough to trigger the…

神经元与认知 · 定量生物学 2019-01-28 Alexander Vidybida

A mechanism is proposed for increasing selectivity of olfactory bulb projection neurons as compared to the olfactory receptor neurons, which could operate under low odor concentration, when the lateral inhibition mechanism becomes…

神经元与认知 · 定量生物学 2021-11-09 Alexander Vidybida

Olfactory receptor usage is highly heterogeneous, with some receptor types being orders of magnitude more abundant than others. We propose an explanation for this striking fact: the receptor distribution is tuned to maximally represent…

神经元与认知 · 定量生物学 2019-01-23 Tiberiu Tesileanu , Simona Cocco , Remi Monasson , Vijay Balasubramanian

On the basis of the evident ability of neuronal olfactory systems to evaluate the intensity of an odorous stimulus and at the same time also recognise the identity of the odorant over a large range of concentrations, a few…

神经元与认知 · 定量生物学 2020-06-29 Carlo Fulvi Mari

Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an…

生物物理 · 物理学 2016-08-26 David Zwicker , Arvind Murugan , Michael P. Brenner

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at organism level the…

分子网络 · 定量生物学 2016-05-11 Xiao-Jun Tian , Hang Zhang , Jens Sannerud , Jianhua Xing

The olfactory sense measures the chemical composition of the environment using a diverse array of olfactory receptors. In vertebrates, the olfactory receptors reside in a mucus layer in the nasal cavity and can thus only detect odorants…

生物物理 · 物理学 2023-01-25 Swati Sen , David Zwicker

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally.…

神经元与认知 · 定量生物学 2022-01-31 David Zwicker

In vertebrates, olfactory sensory neurons choose only one olfactory receptor to produce out of ~2000 possibilities. The mechanism for how this singular receptor expression occurs is unknown. Here we propose a mechanism that can…

分子网络 · 定量生物学 2012-01-16 Brian E. Kolterman , Ivan Iossifov , Alexei A. Koulakov

The olfactory system employs responses of an ensemble of odorant receptors (ORs) to sense molecules and to generate olfactory percepts. Here we hypothesized that ORs can be viewed as 3D spatial filters that extract molecular features…

机器学习 · 计算机科学 2024-12-13 Sergey Shuvaev , Khue Tran , Khristina Samoilova , Cyrille Mascart , Alexei Koulakov

This work presents a general chemical reaction network theory for olfactory sensing processes that employ G-protein-coupled receptors as olfactory receptors (ORs). The theory is applicable to general mixtures of odorants and an arbitrary…

分子网络 · 定量生物学 2023-09-06 Won Kyu Kim , Kiri Choi , Changbong Hyeon , Seogjoo J. Jang

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory…

神经元与认知 · 定量生物学 2024-10-08 Kiri Choi , Will Rosenbluth , Isabella R. Graf , Nirag Kadakia , Thierry Emonet

Our sense of smell relies on sensitive, selective atomic-scale processes that are initiated when a scent molecule meets specific receptors in the nose. However, the physical mechanisms of detection are not clear. While odorant shape and…

生物物理 · 物理学 2015-06-26 Jennifer C. Brookes , Filio Hartoutsiou , A. P. Horsfield , A. M. Stoneham

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: receptors that do not…

神经元与认知 · 定量生物学 2021-09-01 Vijay Singh , Martin Tchernookov , Vijay Balasubramanian

The mammalian brain is a metabolically expensive device, and evolutionary pressures have presumably driven it to make productive use of its resources. For sensory areas, this concept has been expressed more formally as an optimality…

神经元与认知 · 定量生物学 2016-03-02 Deep Ganguli , Eero P. Simoncelli

Odor detection underpins food safety, environmental monitoring, medical diagnostics, and many more fields. The current artificial sensors developed for odor detection struggle with complex mixtures while non-invasive recordings lack…

机器学习 · 计算机科学 2025-08-14 Matin Hassanloo , Ali Zareh , Mehmet Kemal Özdemir

We propose a joint optimal power allocation and sensing threshold selection for capacity maximization at the secondary user (SU) in spectrum sharing (SS) cognitive radio networks (CRNs). Hence, both optimal power allocation (OPA) and…

最优化与控制 · 数学 2012-12-04 F. Foukalas , P. T. Mathiopoulos , G. T. Karetsos

Multivalency is prevalent in various biological systems and applications due to the superselectivity that arises from the cooperativity of multivalent binding. Traditionally, it was thought that weaker individual binding would improve the…

软凝聚态物质 · 物理学 2023-04-13 Xiuyang Xia , Ge Zhang , Massimo Pica Ciamarra , Yang Jiao , Ran Ni
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