Evidence map›Paper›PMID 33229536›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Low rank mechanisms underlying flexible visual representations.

Douglas A Ruff, Cheng Xue, Lily E Kramer, Faisal Baqai, Marlene R Cohen

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. 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
  3. Article
  4. Article
  5. Different roles of response covariability and its attentional modulation in the sensory cortex and posterior parietal cortex.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  6. Topological insights into the neural basis of flexible behavior.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Priority coding in the visual system.Nature reviews. Neuroscience · 2022
    Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. The brain produces mind by modeling.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  16. 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

5 authors at 2 institutions in 1 country.

Douglas A RuffDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260.ORCID 0000-0001-7228-8822
Cheng XueDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260.
Lily E KramerDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260.ORCID 0000-0001-7312-8521
Faisal BaqaiProgram in Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15260.
Marlene R CohenDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260; cohenm@pitt.edu.
University of Pittsburgh · USCarnegie Mellon University · US

Funding

Virus Production and Manipulation of Protein/Gene Expression ModuleP30EY008098 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Ethan A Rossi · 1989 to 2026
$17.8M
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
NEI NIH HHS P30 EY008098NEI NIH HHS R00 EY020844NEI NIH HHS R01 EY022930
6 · The paper itself

Abstract

Neuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex have heterogeneous dependence on stimulus properties (e.g., contrast), processes that affect all stages of visual processing (e.g., adaptation), and cognitive processes (e.g., attention or task switching). Understanding whether these processes affect similar neuronal populations and whether they have similar effects on entire populations can provide insight into whether they utilize analogous mechanisms. In particular, it has recently been demonstrated that attention has low rank effects on the covariability of populations of visual neurons, which impacts perception and strongly constrains mechanistic models. We hypothesized that measuring changes in population covariability associated with other sensory and cognitive processes could clarify whether they utilize similar mechanisms or computations. Our experimental design included measurements in multiple visual areas using four distinct sensory and cognitive processes. We found that contrast, adaptation, attention, and task switching affect the variability of responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit may use similar mechanisms to perform many forms of modulation and likely reflects a general principle that applies to a wide range of brain areas and sensory, cognitive, and motor processes.

Indexed as

Models, NeurologicalAdaptation, OcularAnimalsAttentionCognitionElectrodes, ImplantedMacaca mulattaMaleMicroelectrodesModels, AnimalNerve NetNeuronsPhotic StimulationRetinaVisual CortexVisual Perceptiondimensionalitynormalizationvariabilityvisual cortex

Identifiers

PMID33229536
PMCPMC7703603
OpenAlexW3109025870

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.