ArticlePhysical review. E2021
What the odor is not: Estimation by elimination.
Article in Physical review. E, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Simultaneous detection and estimation in olfactory sensing.bioRxiv : the preprint server for biology · 2025Article
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.bioRxiv : the preprint server for biology · 2025Article
- Slow and steady: auditory features for discriminating animal vocalizations.bioRxiv : the preprint server for biology · 2024Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.bioRxiv : the preprint server for biology · 2023Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.Advances in neural information processing systems · 2023Article
- Efficient processing of natural scenes in visual cortex.Frontiers in cellular neuroscience · 2022Review
- Disorder and the Neural Representation of Complex Odors.Frontiers in computational neuroscience · 2022Article
- Mixture Coding and Segmentation in the Anterior Piriform Cortex.Frontiers in systems neuroscience · 2020Article
- Optimal compressed sensing strategies for an array of nonlinear olfactory receptor neurons with and without spontaneous activity.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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 respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.
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Registered trials
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.