Evidence map›Paper›PMID 26864765›Full record

ArticleJournal of neurophysiology2016

Classification of odorants across layers in locust olfactory pathway.

Pavel Sanda, Tiffany Kee, Nitin Gupta, Mark Stopfer, Maxim Bazhenov

Open access · bronzeAbstract read
In one paragraph

Article in Journal of neurophysiology, 2016. 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
0.8field-weighted citation impact, top 30% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  5. Disorder and the Neural Representation of Complex Odors.Frontiers in computational neuroscience · 2022
    Article
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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

5 authors at 4 institutions in 2 countries.

Pavel SandaDepartment of Medicine, University of California, San Diego, California;
Tiffany KeeDepartment of Medicine, University of California, San Diego, California; Department of Cell Biology and Neuroscience, University of California, Riverside, California;
Nitin GuptaNational Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland; and Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India.
Mark StopferNational Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland; and.
Maxim BazhenovDepartment of Medicine, University of California, San Diego, California; bazhenov@salk.edu.
University of California, San Diego · USEunice Kennedy Shriver National Institute of Child Health and Human Development · USIndian Institute of Technology Kanpur · INUniversity of California, Riverside · US

Funding

Sensory Coding by Ensembles of Neurons.ZIAHD008760 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI STOPFER, MARK A · 2009 to 2025
$26.3M
CRCNS: Dyanamic and Distributed Memory in OlfactionR01DC011422 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HUERTA, RAMON · 2010 to 2014
$1.7M
CRCNS: Multiple roles of inhibition in the olfactory systemR01DC012943 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAZHENOV, MAKSIM V · 2012 to 2016
$1.3M
NIDCD NIH HHS R01 DC011422NIDCD NIH HHS R01 DC012943
6 · The paper itself

Abstract

Olfactory processing takes place across multiple layers of neurons from the transduction of odorants in the periphery, to odor quality processing, learning, and decision making in higher olfactory structures. In insects, projection neurons (PNs) in the antennal lobe send odor information to the Kenyon cells (KCs) of the mushroom bodies and lateral horn neurons (LHNs). To examine the odor information content in different structures of the insect brain, antennal lobe, mushroom bodies and lateral horn, we designed a model of the olfactory network based on electrophysiological recordings made in vivo in the locust. We found that populations of all types (PNs, LHNs, and KCs) had lower odor classification error rates than individual cells of any given type. This improvement was quantitatively different from that observed using uniform populations of identical neurons compared with spatially structured population of neurons tuned to different odor features. This result, therefore, reflects an emergent network property. Odor classification improved with increasing stimulus duration: for similar odorants, KC and LHN ensembles reached optimal discrimination within the first 300-500 ms of the odor response. Performance improvement with time was much greater for a population of cells than for individual neurons. We conclude that, for PNs, LHNs, and KCs, ensemble responses are always much more informative than single-cell responses, despite the accumulation of noise along with odor information.

Indexed as

Discrimination, PsychologicalOlfactory PerceptionAnimalsGrasshoppersMushroom BodiesOdorantsOlfactory PathwaysSensory Receptor Cellslocust olfactionnetwork modelodor concentrationodor discrimination

Identifiers

PMID26864765
PMCPMC4922456
OpenAlexW2260759105

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.