Evidence map›Paper›PMID 30076307›Full record

ArticleNature communications2018

Dynamic contrast enhancement and flexible odor codes.

Srinath Nizampatnam, Debajit Saha, Rishabh Chandak, Baranidharan Raman

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Conserved neural dynamics and computations across species in olfaction.bioRxiv : the preprint server for biology · 2023
    Article
  8. Article
  9. Article
  10. Invariant odor recognition with ON-OFF neural ensembles.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  11. Habituation as a neural algorithm for online odor discrimination.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  12. Neural Circuit Dynamics for Sensory Detection.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020
    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

4 authors.

Srinath NizampatnamDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, 63130, USA.
Debajit SahaDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, 63130, USA.
Rishabh ChandakDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, 63130, USA.ORCID http://orcid.org/0000-0001-9984-3312
Baranidharan RamanDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, 63130, USA. barani@wustl.edu.ORCID http://orcid.org/0000-0002-7866-155X

Funding

DOD | ONR | Office of Naval Research Global (ONR Global) N000141612426National Science Foundation (NSF) 1453022
6 · The paper itself

Abstract

Sensory stimuli evoke spiking activities patterned across neurons and time that are hypothesized to encode information about their identity. Since the same stimulus can be encountered in a multitude of ways, how stable or flexible are these stimulus-evoked responses? Here we examine this issue in the locust olfactory system. In the antennal lobe, we find that both spatial and temporal features of odor-evoked responses vary in a stimulus-history dependent manner. The response variations are not random, but allow the antennal lobe circuit to enhance the uniqueness of the current stimulus. Nevertheless, information about the odorant identity is conf ounded due to this contrast enhancement computation. Notably, predictions from a linear logical classifier (OR-of-ANDs) that can decode information distributed in flexible subsets of neurons match results from behavioral experiments. In sum, our results suggest that a trade-off between stability and flexibility in sensory coding can be achieved using a simple computational logic.

Indexed as

OdorantsAction PotentialsAnimalsBehavior, AnimalClinical CodingElectric StimulationGrasshoppersModels, NeurologicalOlfactory PathwaysOlfactory PerceptionOlfactory Receptor NeuronsSmellSupport Vector Machine

Identifiers

PMID30076307
PMCPMC6076288

What OpenQuestion holds

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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.