Evidence map›Paper›PMID 32031520›Full record

ArticleeLife2020

The contribution of temporal coding to odor coding and odor perception in humans.

Ofer Perl, Nahum Nahum, Katya Belelovsky, Rafi Haddad

Abstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Survey of temporal coding of sensory information.Frontiers in computational neuroscience · 2025
    Article
  3. Timing matters in olfaction.Nature human behaviour · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Coupling of Mouse Olfactory Bulb Projection Neurons to Fluctuating Odor Pulses.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  8. Review
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

4 authors.

Ofer PerlThe Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.ORCID 0000-0002-3560-4344
Nahum NahumDepartment of Psychology, Bar-Ilan University, Ramat-Gan, Israel.
Katya BelelovskyThe Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.ORCID 0000-0001-9960-7336
Rafi HaddadThe Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.ORCID 0000-0001-8285-5210

Funding

Israel Science Foundation 204/17
6 · The paper itself

Abstract

Whether neurons encode information through their spike rates, their activity times or both is an ongoing debate in systems neuroscience. Here, we tested whether humans can discriminate between a pair of temporal odor mixtures (TOMs) composed of the same two components delivered in rapid succession in either one temporal order or its reverse. These TOMs presumably activate the same olfactory neurons but at different times and thus differ mainly in the time of neuron activation. We found that most participants could hardly discriminate between TOMs, although they easily discriminated between a TOM and one of its components. By contrast, participants succeeded in discriminating between the TOMs when they were notified of their successive nature in advance. We thus suggest that the time of glomerulus activation can be exploited to extract odor-related information, although it does not change the odor perception substantially, as should be expected from an odor code per se.

Indexed as

Models, NeurologicalAdolescentAdultFemaleHumansMaleOdorantsOlfactory BulbOlfactory PerceptionTime FactorsYoung Adultcodinghumanneuroscienceodor perceptionolfactionpsychophysicstemporal coding

Identifiers

PMID32031520
PMCPMC7007219

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.