ReviewFrontiers in neuroscience2023
Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies.
Review in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 36 citations in OpenAlex.
- Measuring electroretinograms in tree shrews with a portable electrophysiology device.Documenta ophthalmologica. Advances in ophthalmology · 2026Article
- Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Visual function and autism spectrum disorder.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Improving Parkinson's disease diagnosis by non-invasive detection of retinal biomarkers in MPTP monkeys using ERG and pupillometry.NPJ Parkinson's disease · 2026Article
- ERG-Graph: Graph Signal Processing of the Electroretinogram for Classification of Neurodevelopmental Disorders.Bioengineering (Basel, Switzerland) · 2026Article
- Electroretinography as a non-invasive biomarker for early detection of cognitive impairment in older adults: A scoping review protocol.PloS one · 2026Article
- Disruption of estrogen signaling by developmental exposure to BPA and TBT causes long term functional deficits in zebrafish retina.Frontiers in pharmacology · 2026Review
- The reproducibility of handheld ERGs recorded with skin electrode and natural pupils.Documenta ophthalmologica. Advances in ophthalmology · 2025Article
- Synthetic electroretinogram signal generation using a conditional generative adversarial network.Documenta ophthalmologica. Advances in ophthalmology · 2025Article
- Time Series Classification of Autism Spectrum Disorder Using the Light-Adapted Electroretinogram.Bioengineering (Basel, Switzerland) · 2025Article
- Reduced contrast sensitivity, pattern electroretinogram ratio, and diminished a-wave amplitude in patients with major depressive disorder.European archives of psychiatry and clinical neuroscience · 2025Article
- Retinal fundus imaging as biomarker for ADHD using machine learning for screening and visual attention stratification.NPJ digital medicine · 2025Article
- Brief report: effects of methylphenidate on the light adapted electroretinogram.Documenta ophthalmologica. Advances in ophthalmology · 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
- Electroretinogram Analysis Using a Short-Time Fourier Transform and Machine Learning Techniques.Bioengineering (Basel, Switzerland) · 2024Article
- Commentary: Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies.Frontiers in neuroscience · 2024Article
- Generating Synthetic Light-Adapted Electroretinogram Waveforms Using Artificial Intelligence to Improve Classification of Retinal Conditions in Under-Represented Populations.Journal of ophthalmology · 2024Article
- Enhancing Electroretinogram Classification with Multi-Wavelet Analysis and Visual Transformer.Sensors (Basel, Switzerland) · 2023Article
- Group comparisons of the individual electroretinogram time trajectories for the ascending limb of the b-wave using a raw and registered time series.BMC research notes · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The retina and brain share similar neurochemistry and neurodevelopmental origins, with the retina, often viewed as a "window to the brain." With retinal measures of structure and function becoming easier to obtain in clinical populations there is a growing interest in using retinal findings as potential biomarkers for disorders affecting the central nervous system. Functional retinal biomarkers, such as the electroretinogram, show promise in neurological disorders, despite having limitations imposed by the existence of overlapping genetic markers, clinical traits or the effects of medications that may reduce their specificity in some conditions. This narrative review summarizes the principal functional retinal findings in central nervous system disorders and related mouse models and provides a background to the main excitatory and inhibitory retinal neurotransmitters that have been implicated to explain the visual electrophysiological findings. These changes in retinal neurochemistry may contribute to our understanding of these conditions based on the findings of retinal electrophysiological tests such as the flash, pattern, multifocal electroretinograms, and electro-oculogram. It is likely that future applications of signal analysis and machine learning algorithms will offer new insights into the pathophysiology, classification, and progression of these clinical disorders including autism, attention deficit/hyperactivity disorder, bipolar disorder, schizophrenia, depression, Parkinson's, and Alzheimer's disease. New clinical applications of visual electrophysiology to this field may lead to earlier, more accurate diagnoses and better targeted therapeutic interventions benefiting individual patients and clinicians managing these individuals and their families.
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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.