ArticleProceedings of the National Academy of Sciences of the United States of America1999
Odor space and olfactory processing: collective algorithms and neural implementation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed, 121 citations in OpenAlex.
- The primacy model and the structure of olfactory space.PLoS computational biology · 2024Article
- A new conceptual and quantitative approach to exploring and defining potential open-access olfactory information.The New phytologist · 2022Article
- What the odor is not: Estimation by elimination.Physical review. E · 2021Article
- Rapid Bayesian learning in the mammalian olfactory system.Nature communications · 2020Article
- Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice.Nature communications · 2020Article
- A molecular odorant transduction model and the complexity of spatio-temporal encoding in the Drosophila antenna.PLoS computational biology · 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
- Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned.PLoS computational biology · 2019Article
- Genetic codes optimized as a traveling salesman problem.PloS one · 2019Article
- Implications for human odor sensing revealed from the statistics of odorant-receptor interactions.PLoS computational biology · 2018Article
- Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures.eLife · 2018Article
- An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems.Sensors (Basel, Switzerland) · 2017Review
- A probabilistic approach to demixing odors.Nature neuroscience · 2017Article
- Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing.Neuron · 2016Article
- Receptor arrays optimized for natural odor statistics.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Normalized Neural Representations of Complex Odors.PloS one · 2016Article
- An olfactory cocktail party: figure-ground segregation of odorants in rodents.Nature neuroscience · 2014Article
- Intermittency coding in the primary olfactory system: a neural substrate for olfactory scene analysis.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014Article
- A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system.Frontiers in neural circuits · 2014Article
- Multiple perceptible signals from a single olfactory glomerulus.Nature neuroscience · 2013Article
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1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Several basic olfactory tasks must be solved by highly olfactory animals, including background suppression, multiple object separation, mixture separation, and source identification. The large number N of classes of olfactory receptor cells-hundreds or thousands-permits the use of computational strategies and algorithms that would not be effective in a stimulus space of low dimension. A model of the patterns of olfactory receptor responses, based on the broad distribution of olfactory thresholds, is constructed. Representing one odor from the viewpoint of another then allows a common description of the most important basic problems and shows how to solve them when N is large. One possible biological implementation of these algorithms uses action potential timing and adaptation as the "hardware" features that are responsible for effective neural computation.
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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.