ArticleScientific reports2016
Predicting the response of olfactory sensory neurons to odor mixtures from single odor response.
Article in Scientific reports, 2016. 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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Who cites it
6 citing papers in PubMed.
- Article
- The primacy model and the structure of olfactory space.PLoS computational biology · 2024Article
- Widespread receptor-driven modulation in peripheral olfactory coding.Science (New York, N.Y.) · 2020Article
- Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Odorant mixtures elicit less variable and faster responses than pure odorants.PLoS computational biology · 2018Article
- Glomerular and Mitral-Granule Cell Microcircuits Coordinate Temporal and Spatial Information Processing in the Olfactory Bulb.Frontiers in computational neuroscience · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.