Evidence map›Paper›PMID 40668063›Full record

ReviewJournal of vision2025

Human retinotopic mapping: From empirical to computational models of retinotopy.

Fernanda L Ribeiro, Noah C Benson, Alexander M Puckett

Abstract readReview
In one paragraph

Review in Journal of vision, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. qPRF: A system to accelerate population receptive field decoding.bioRxiv : the preprint server for biology · 2024
    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.

Fernanda L RibeiroSchool of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia.
Noah C BensoneScience Institute, University of Washington, Seattle, WA, USA.
Alexander M PuckettSchool of Psychology, The University of Queensland, Brisbane, Queensland, Australia.

Funding

CRCNS: Integrating gray and white matter data to understand the organization of human visual cortexR01EY033628 · NEI · UNIVERSITY OF WASHINGTON · PI Noah C Benson, JONATHAN A WINAWER · 2021 to 2026
$1.7M
NEI NIH HHS R01 EY033628
6 · The paper itself

Abstract

The visual cortex encodes the visual field through numerous bilaterally paired, topologically organized two-dimensional maps along the cortical surface. Although these representations exhibit a largely consistent organization across individuals, substantial interindividual variability exists in both the structure and functional organization of the visual cortex. To better characterize this variability, researchers have increasingly turned to computational approaches, alongside empirical methodologies and encoding models, to predict individual-level retinotopic organization. As these advances continue to shape the study of retinotopic organization, it is crucial to revisit the methodologies used to generate and model these maps. In this review, we examine empirical and theoretical work aimed at reconstructing and modeling visual field maps in the human visual cortex. Specifically, we discuss how empirical retinotopic mapping has facilitated the development of theoretical and computational models of retinotopy and, in turn, how these models have enhanced our understanding of the retinotopic organization of the human visual cortex. Finally, we outline a non-exhaustive set of future directions for leveraging models of retinotopy to further investigate structure-function relationships, interindividual variability, and more.

Indexed as

Brain MappingComputer SimulationModels, NeurologicalRetinaVisual CortexVisual FieldsVisual PathwaysHumans

Identifiers

PMID40668063
PMCPMC12279071

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.