Evidence map›Paper›PMID 38374462›Full record

ReviewNature reviews. Neuroscience2024

Response sub-additivity and variability quenching in visual cortex.

Robbe L T Goris, Ruben Coen-Cagli, Kenneth D Miller, Nicholas J Priebe, Máté Lengyel

Abstract readReview
In one paragraph

Review in Nature reviews. Neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. The human language processing system straightens natural speech.bioRxiv : the preprint server for biology · 2026
    Article
  2. The time-intensity uncertainty principle in vision.Attention, perception & psychophysics · 2026
    Article
  3. Article
  4. Article
  5. Computational and Neuronal Basis of Visual Confidence.Annual review of vision science · 2025
    Review
  6. Article
  7. Sensory population activity reveals downstream confidence computations in the primate visual system.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. 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.

Robbe L T GorisCenter for Perceptual Systems, University of Texas at Austin, Austin, TX, USA. Robbe.Goris@utexas.edu.ORCID http://orcid.org/0000-0002-2218-3720
Ruben Coen-CagliDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA.ORCID http://orcid.org/0000-0003-2052-5894
Kenneth D MillerCenter for Theoretical Neuroscience, Columbia University, New York, NY, USA.ORCID http://orcid.org/0000-0002-1433-0647
Nicholas J PriebeCenter for Learning and Memory, University of Texas at Austin, Austin, TX, USA.ORCID http://orcid.org/0000-0002-0171-0691
Máté LengyelComputational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-7266-0049

Funding

Validating Theoretical Models with Neurophysiology and OptogeneticsU19NS107613 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MILLER, KENNETH D · 2018 to 2022
$16.7M
Cortical mechanisms mediating visual function and behaviorR01EY024071 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI PRIEBE, NICHOLAS J, SEIDEMANN, EYAL J · 2014 to 2025
$4.1M
Excitation and inhibition in visual processingR01EY025102 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI PRIEBE, NICHOLAS J · 2014 to 2023
$3.1M
Natural image processing in the visual cortexR01EY030578 · NEI · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Ruben Coen-Cagli, ADAM KOHN · 2019 to 2026
$2.9M
Circuitry underlying response summation in mouse and primate: Theory and experimentU01NS108683 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI BRUNEL, NICOLAS, MILLER, KENNETH D · 2018 to 2020
$2.8M
Uncertainty, inference, and introspection in the primate visual systemR01EY032999 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI GORIS, ROBBE L · 2022 to 2025
$1.6M
Computational Tools for assessing mechanisms and functional relevance of divisive normalizationRF1DA056400 · NIDA · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI COEN-CAGLI, RUBEN · 2022 to 2022
$1.2M
CRCNS: Integrating sensory and prior information to control behaviorR01NS120562 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI PRIEBE, NICHOLAS J · 2020 to 2023
$1.1M
NEI NIH HHS R01 EY024071NEI NIH HHS R01 EY025102NEI NIH HHS R01 EY030578NEI NIH HHS R01 EY032999NIDA NIH HHS RF1 DA056400NINDS NIH HHS R01 NS120562NINDS NIH HHS U01 NS108683NINDS NIH HHS U19 NS107613Wellcome Trust 212262/Z/18/Z
6 · The paper itself

Abstract

Sub-additivity and variability are ubiquitous response motifs in the primary visual cortex (V1). Response sub-additivity enables the construction of useful interpretations of the visual environment, whereas response variability indicates the factors that limit the precision with which the brain can do this. There is increasing evidence that experimental manipulations that elicit response sub-additivity often also quench response variability. Here, we provide an overview of these phenomena and suggest that they may have common origins. We discuss empirical findings and recent model-based insights into the functional operations, computational objectives and circuit mechanisms underlying V1 activity. These different modelling approaches all predict that response sub-additivity and variability quenching often co-occur. The phenomenology of these two response motifs, as well as many of the insights obtained about them in V1, generalize to other cortical areas. Thus, the connection between response sub-additivity and variability quenching may be a canonical motif across the cortex.

Indexed as

Visual CortexBrainHumansPhotic StimulationVisual Pathways

Identifiers

PMID38374462
PMCPMC11444047

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.