Evidence map›Paper›PMID 26523390›Full record

ArticleeLife2015

Attention stabilizes the shared gain of V4 populations.

Neil C Rabinowitz, Robbe L Goris, Marlene Cohen, Eero P Simoncelli

Abstract read
In one paragraph

Article in eLife, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers.

0numbers the graph read from it
0cells of the map it votes in
113citing 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

113 citing papers in PubMed.

  1. Article
  2. The human language processing system straightens natural speech.bioRxiv : the preprint server for biology · 2026
    Article
  3. The time-intensity uncertainty principle in vision.Attention, perception & psychophysics · 2026
    Article
  4. Article
  5. Article
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  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Recent Visual Experience Reshapes V4 Neuronal Activity and Improves Perceptual Performance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Article

53 more citing papers are in PubMed but not listed here.

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.

Neil C RabinowitzCenter for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.
Robbe L GorisCenter for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.
Marlene CohenDepartment of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, United States.
Eero P SimoncelliCenter for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.

Funding

Using Neuronal Populations to Probe Perceptual DecisionsR01EY022930 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COHEN, MARLENE ROCHELLE · 2013 to 2022
$3.8M
Using Attention to Understand Cortical Population CodesR00EY020844 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COHEN, MARLENE ROCHELLE · 2011 to 2013
$730k
Howard Hughes Medical InstituteNEI NIH HHS 4R00EY020844-03NEI NIH HHS R01 EY022930
6 · The paper itself

Abstract

Responses of sensory neurons represent stimulus information, but are also influenced by internal state. For example, when monkeys direct their attention to a visual stimulus, the response gain of specific subsets of neurons in visual cortex changes. Here, we develop a functional model of population activity to investigate the structure of this effect. We fit the model to the spiking activity of bilateral neural populations in area V4, recorded while the animal performed a stimulus discrimination task under spatial attention. The model reveals four separate time-varying shared modulatory signals, the dominant two of which each target task-relevant neurons in one hemisphere. In attention-directed conditions, the associated shared modulatory signal decreases in variance. This finding provides an interpretable and parsimonious explanation for previous observations that attention reduces variability and noise correlations of sensory neurons. Finally, the recovered modulatory signals reflect previous reward, and are predictive of subsequent choice behavior.

Indexed as

AttentionPerceptionAction PotentialsAnimalsHaplorhiniModels, NeurologicalSensory Receptor Cellsattentioncomputationcomputational biologyneurosciencesensorystatisticssystems biologyvision

Identifiers

PMID26523390
PMCPMC4758958

What OpenQuestion holds

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LicenceCC BY
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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.