Native components analysis of the spectral electroretinogram.

Christopher W Tyler, Michael Liang, Zhangziyi Zhou, Lora T Likova

Abstract read

In one paragraph

Article in Vision research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Christopher W TylerSmith-Kettlewell Brain Imaging Center, Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco CA 94115, USA; Optometry and Vision Sciences, City-St Georges, Northampton Square, University of London, London EC1, UK. Electronic address: cwt@ski.org.

Michael LiangSmith-Kettlewell Brain Imaging Center, Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco CA 94115, USA; Optometry and Vision Sciences, City-St Georges, Northampton Square, University of London, London EC1, UK.

Zhangziyi ZhouSmith-Kettlewell Brain Imaging Center, Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco CA 94115, USA; Optometry and Vision Sciences, City-St Georges, Northampton Square, University of London, London EC1, UK.

Lora T LikovaSmith-Kettlewell Brain Imaging Center, Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco CA 94115, USA; Optometry and Vision Sciences, City-St Georges, Northampton Square, University of London, London EC1, UK.

Funding

Spectral ERG Analysis of Hypersensitivity to Light in Traumatic Brain InjuryR01EY030155 · NEI · SMITH-KETTLEWELL EYE RESEARCH INSTITUTE · PI TYLER, CHRISTOPHER W · 2020 to 2022

$1.2M

NEI NIH HHS R01 EY030155

6 · The paper itself

Abstract

The electroretinogram (ERG) is a mass electrical response from all electrically activated components of the retina, recorded with the goal of identifying the individual contributions of relevant components for the purposes of electrodiagnosis of eye diseases and other systemic medical conditions. The primary hypothesis being tested was that the ERGs across the spectrum in the mesopic range of intensities could be fully accounted with a duplex (two-component) model of linear combinations of rod- and cone-pathway responses. Full-field square-wave ERGs were measured with the RETeval device at 2 Hz for 7 spectral bands: red, yellow, green, cyan, blue, magenta, and white, in increasing steps of 0.5 log units from 3 to 300 phot cd/m

Indexed as

ElectroretinographyRetinaAdultFemaleHumansMalePhotic StimulationRetinal Cone Photoreceptor CellsRetinal Rod Photoreceptor CellsYoung AdultColorComponentsElectroretinogramModelingPCARetinaSpectral

Identifiers

PMID40749534

DOI10.1016/j.visres.2025.108661

PMCPMC12573766

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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.