ArticleBMC research notes2023
Group comparisons of the individual electroretinogram time trajectories for the ascending limb of the b-wave using a raw and registered time series.
Article in BMC research notes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Lycium barbarum polysaccharide as a retinoprotective agent: A meta-analysis of preclinical evidence from rodent models of retinopathy.Neural regeneration research · 2026Article
- Technical note: a functional data analysis approach to analyze the light-adapted electroretinogram in children and adolescents.Documenta ophthalmologica. Advances in ophthalmology · 2026Article
- ERG-Graph: Graph Signal Processing of the Electroretinogram for Classification of Neurodevelopmental Disorders.Bioengineering (Basel, Switzerland) · 2026Article
- Technical note: contour plot visualization of the light adapted electroretinogram using a generalized additive model.Documenta ophthalmologica. Advances in ophthalmology · 2026Article
- Time Series Classification of Autism Spectrum Disorder Using the Light-Adapted Electroretinogram.Bioengineering (Basel, Switzerland) · 2025Article
- Remodeling the light-adapted electroretinogram using a bayesian statistical approach.BMC research notes · 2025Article
- Spectral Analysis of Light-Adapted Electroretinograms in Neurodevelopmental Disorders: Classification with Machine Learning.Bioengineering (Basel, Switzerland) · 2024Article
- Generating Synthetic Light-Adapted Electroretinogram Waveforms Using Artificial Intelligence to Improve Classification of Retinal Conditions in Under-Represented Populations.Journal of ophthalmology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe electroretinogram is a clinical test commonly used in the diagnosis of retinal disorders with the peak time and amplitude of the a- and b-waves used as the main indicators of retinal function. However, subtle changes that affect the shape of the electroretinogram waveform may occur in the early stages of disease or in conditions that have a neurodevelopmental or neurodegenerative origin. In such cases, we introduce a statistical approach to mathematically model the shape of the electroretinogram waveform that may aid clinicians and researchers using the electroretinogram or other biological signal recordings to identify morphological features in the waveforms that may not be captured by the time or time-frequency domains of the waveforms. We present a statistical graphics-based analysis of the ascending limb of the b-wave (AL-b) of the electroretinogram in children with and without a diagnosis of autism spectrum disorder (ASD) with a narrative explanation of the statistical approach to illustrate how different features of the waveform based on location and scale derived from raw and registered time series can reveal subtle differences between the groups.
resultsAnalysis of the raw time trajectories confirmed findings of previous studies with a reduced and delayed b-wave amplitude in ASD. However, when the individual time trajectories were registered then group differences were visible in the mean amplitude at registered time ~ 0.6 suggesting a novel method to differentiate groups using registration of the ERG waveform.
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Registered trials
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.