Evidence map›Paper›PMID 27102871›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2016

Receptor arrays optimized for natural odor statistics.

David Zwicker, Arvind Murugan, Michael P Brenner

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
  2. 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 · 2026
    Article
  3. Simultaneous detection and estimation in olfactory sensing.bioRxiv : the preprint server for biology · 2025
    Article
  4. When noncanonical olfaction is optimal.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Nonequilibrium sensing of volatile compounds using active and passive analyte delivery.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  10. Article
  11. Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.Advances in neural information processing systems · 2023
    Article
  12. Article
  13. Disorder and the Neural Representation of Complex Odors.Frontiers in computational neuroscience · 2022
    Article
  14. Article
  15. Article
  16. Nonlinear convergence boosts information coding in circuits with parallel outputs.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  17. Article
  18. 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 · 2019
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

David ZwickerSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138; Kavli Institute for Bionano Science and Technology, Harvard University, Cambridge, MA 02138;
Arvind MuruganSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138; Kavli Institute for Bionano Science and Technology, Harvard University, Cambridge, MA 02138; Department of Physics, University of Chicago, Chicago, IL 60637; James Franck Institute, University of Chicago, Chicago, IL 60637 brenner@seas.harvard.edu amurugan@uchicago.edu.
Michael P BrennerSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138; Kavli Institute for Bionano Science and Technology, Harvard University, Cambridge, MA 02138; brenner@seas.harvard.edu amurugan@uchicago.edu.

Funding

KITP Interdisciplinary Biology InitiativeR25GM067110 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI SHRAIMAN, BORIS I · 2003 to 2018
$1.8M
NIGMS NIH HHS R25 GM067110
6 · The paper itself

Abstract

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 information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.

Indexed as

BiometryOdorantsHumansInformation TheoryReceptors, OdorantSmellReceptors, Odorantinformation theorymolecular recognitionnatural statisticsolfactionsensing

Identifiers

PMID27102871
PMCPMC4878513

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.