Evidence map›Paper›PMID 41270154›Full record

ArticlePLoS computational biology2025

Universal scale-free representations in human visual cortex.

Raj Magesh Gauthaman, Brice Ménard, Michael F Bonner

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  2. The Emergence of Topography and Hemispheric Lateralization in High-Level Vision.Quarterly journal of experimental psychology (2006) · 2026
    Review
  3. Review
  4. Article
  5. 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.

Raj Magesh GauthamanDepartment of Cognitive Science, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID 0000-0001-7121-1532
Brice MénardDepartment of Cognitive Science, Johns Hopkins University, Baltimore, Maryland, United States of America.
Michael F BonnerDepartment of Cognitive Science, Johns Hopkins University, Baltimore, Maryland, United States of America.

Funding

Institute for Data Intensive Engineering and ScienceJohns Hopkins Catalyst AwardKavli Institute for Theoretical Physics
6 · The paper itself

Abstract

How does the human brain encode complex visual information? While previous research has characterized individual dimensions of visual representation in cortex, we still lack a comprehensive understanding of how visual information is organized across the full range of neural population activity. Here, analyzing fMRI responses to natural scenes across multiple individuals, we discover that neural representations in human visual cortex follow a remarkably consistent scale-free organization-their variance decay is consistent with a power-law distribution, detected across four orders of magnitude of latent dimensions. This scale-free structure appears consistently across multiple visual regions and across individuals, suggesting it reflects a fundamental organizing principle of visual processing. Critically, when we align neural responses across individuals using hyperalignment, we find that these representational dimensions are largely shared between people, revealing a universal high-dimensional spectrum of visual information that emerges despite individual differences in brain anatomy and visual experience. Traditional analysis approaches in cognitive neuroscience have focused primarily on a small number of high-variance dimensions, potentially missing crucial aspects of visual representation. Our results demonstrate that visual information is distributed across the full dimensionality of cortical activity in a systematic way, thus revealing a key property of neural coding in visual cortex. These findings suggest that we need to move beyond low-dimensional characterizations to fully understand how the brain represents the visual world.

Indexed as

Visual CortexVisual PerceptionAdultBrain MappingComputational BiologyFemaleHumansMagnetic Resonance ImagingMaleModels, NeurologicalYoung Adult

Identifiers

PMID41270154
PMCPMC12654933

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.