Evidence map›Paper›PMID 36473436›Full record

ArticleCurrent biology : CB2022

Olfactory coding.

George Barnum, Elizabeth J Hong

Abstract read
In one paragraph

Article in Current biology : CB, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

George BarnumDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Elizabeth J HongDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA. Electronic address: ejhong@caltech.edu.
California Institute of Technology · US

Funding

Tracing Brain Circuits by Transneuronal Control of TranscriptionU01MH109147 · NIMH · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI HONG, ELIZABETH JENNIFER, LOIS, CARLOS · 2015 to 2017
$3.1M
Predoctoral Training in Quantitative NeuroscienceT32NS105595 · NINDS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI MARKUS MEISTER · 2019 to 2026
$2.6M
NIMH NIH HHS U01 MH109147NINDS NIH HHS T32 NS105595
6 · The paper itself

Abstract

Modern humans live in real and digital environments dominated by sight and sound, but the vast majority of organisms on the planet rely on information received through air- or water-borne molecules to find food, avoid danger, and reproduce. Olfaction is at once both the primitive sensory modality and one of the hardest to understand, in large part due to the complexity of olfactory stimulus space. Whereas light and sound are easily ordered along natural physical axes that are reflected in their respective sensory codes, the organizational axes of odor space are not obvious. The search for systematic relationships between physicochemical characteristics of monomolecular odorants (carbon chain length, bond numbers, functional groups, etc.) and human perception of odorants suggests that olfactory perceptual space is a relatively low-dimensional structure. Odor descriptors provided by human observers are often significantly correlated. For instance, odors perceived as 'woody' are also likely to be described as 'warm', and many studies converge on hedonic valence or 'pleasantness' as being one of the most important dimensions of how people perceive odors. The identification of additional perceptual 'primaries' around which olfaction is organized is an active area of investigation, and a useful account of olfactory coding must explain this transformation of odor stimuli from the high dimensional chemical space to a lower dimensional perceptual space.

Identifiers

PMID36473436
PMCPMC13084759
OpenAlexW4310861174

What OpenQuestion holds

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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.