Evidence map›Paper›PMID 34634035›Full record

ArticlePLoS computational biology2021

Cortical feedback and gating in odor discrimination and generalization.

Gaia Tavoni, David E Chen Kersen, Vijay Balasubramanian

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Connectivity and dynamics in the olfactory bulb.PLoS computational biology · 2022
    Article
  3. Disorder and the Neural Representation of Complex Odors.Frontiers in computational neuroscience · 2022
    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.

Gaia TavoniComputational Neuroscience Initiative, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0001-5538-3633
David E Chen KersenComputational Neuroscience Initiative, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0003-4292-5100
Vijay BalasubramanianComputational Neuroscience Initiative, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-6497-3819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.

Indexed as

Models, NeurologicalAlzheimer DiseaseBrainComputational BiologyFeedback, PhysiologicalHumansOlfactory PathwaysOlfactory Perception

Identifiers

PMID34634035
PMCPMC8530364

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.