Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies

Frontiers in Neuroscience

Neuroscience

Paul A. Constable¹  Jeremiah K. H. Lim²  Dorothy A. Thompson³ 

[1] College of Nursing and Health Sciences, Caring Futures Institute, Flinders University, Adelaide, SA, Australia;Discipline of Optometry, School of Allied Health, University of Western Australia, Perth, WA, Australia;The Tony Kriss Visual Electrophysiology Unit, Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom;UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom;

关键词: psychiatry;    retinal biomarkers;    retina;    PERG;    electro-oculogram;    electroretinogram;    central nervous system;    ERG;   

DOI  :  10.3389/fnins.2023.1215097

 received in 2023-05-01, accepted in 2023-07-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

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Copyright © 2023 Constable, Lim and Thompson.