Evidence map›Paper›PMID 34293295›Full record

ArticleNeuron2021

Bridging neuronal correlations and dimensionality reduction.

Akash Umakantha, Rudina Morina, Benjamin R Cowley, Adam C Snyder, Matthew A Smith, Byron M Yu

Abstract read
In one paragraph

Article in Neuron, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Loss of neuronal population organization links pathology to behavior in a model of Alzheimer's disease.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Neural Dynamics in Extrastriate Cortex Underlying False Alarms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  10. In vivo microelectrode arrays for neuroscience.Nature reviews. Methods primers · 2025
    Article
  11. Article
  12. 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
  13. Article
  14. Article
  15. Article
  16. Nonlinear manifolds underlie neural population activity during behaviour.bioRxiv : the preprint server for biology · 2024
    Article
  17. Article
  18. Article
  19. Compact deep neural network models of visual cortex.bioRxiv : the preprint server for biology · 2023
    Article
  20. 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

6 authors.

Akash UmakanthaCarnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Rudina MorinaDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Benjamin R CowleyMachine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
Adam C SnyderDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14642, USA; Department of Neuroscience, University of Rochester, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, Rochester, NY 14642, USA.
Matthew A SmithCarnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: mattsmith@cmu.edu.
Byron M YuCarnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: byronyu@cmu.edu.

Funding

Virus Production and Manipulation of Protein/Gene Expression ModuleP30EY008098 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Marlene Behrmann · 1989 to 2026
$17.8M
Shaping Neural Population Dynamics to Facilitate LearningR01HD071686 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BATISTA, AARON PAUL, CHASE, STEVEN M · 2011 to 2021
$3.7M
Interrogating and Perturbing Neural DynamicsR01NS105318 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Aaron Paul Batista, Steven M Chase · 2017 to 2026
$2.3M
Slow time scale fluctuations in neurons and behaviorR01MH128393 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI MATTHEW A SMITH · 2022 to 2026
$2.2M
Dynamic Mechanisms of active vision in prefrontal cortexR01EY022928 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SMITH, MATTHEW A · 2014 to 2018
$1.9M
CRCNS: Modulating Neural Population Interactions between Cortical AreasR01MH118929 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A, YU, BYRON M. · 2018 to 2022
$1.7M
Dynamic population codes for perceptionR01EY029250 · NEI · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A · 2020 to 2023
$1.3M
Neuronal population dynamics within and across cortical areasR01EB026953 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DOIRON, BRENT D., SMITH, MATTHEW A · 2018 to 2020
$1.0M
CRCNS: Interhemispheric coordination for memory and actionR01NS147766 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI Joseph Patrick Mayo, MATTHEW A SMITH · 2025 to 2026
$750k
High-dimensional analysis of selective visual attention mechanismsR00EY025768 · NEI · UNIVERSITY OF ROCHESTER · PI SNYDER, ADAM CHRISTOPHER · 2018 to 2020
$744k
Identifying selective visual attention mechanisms through high-dimensional analysis.K99EY025768 · NEI · CARNEGIE-MELLON UNIVERSITY · PI SNYDER, ADAM CHRISTOPHER · 2015 to 2016
$196k
NEI NIH HHS K99 EY025768NEI NIH HHS P30 EY008098NEI NIH HHS R00 EY025768NEI NIH HHS R01 EY022928NEI NIH HHS R01 EY029250NIBIB NIH HHS R01 EB026953NICHD NIH HHS R01 HD071686NIMH NIH HHS R01 MH118929NIMH NIH HHS R01 MH128393NINDS NIH HHS R01 NS105318NINDS NIH HHS R01 NS147766
6 · The paper itself

Abstract

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. Although both approaches have been used to study trial-to-trial neuronal variability correlated among neurons, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.

Indexed as

Models, NeurologicalSpatial ProcessingAction PotentialsAnimalsAttentionMacaca mulattaNeuronsVisual Cortexdimensionality reductionneuronal populationspatial attentionspike count correlationvisual area V4

Identifiers

PMID34293295
PMCPMC8505167

What OpenQuestion holds

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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.