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The full-field electroretinogram (ERG) is a mass electrophysiological response to diffuse flashes of light and is used widely to assess generalized retinal function. This document, from the International Society for Clinical Electrophysiology of Vision (ISCEV), presents an updated and revised ISCEV Standard for clinical ERG testing. Minimum protocols for basic ERG stimuli, recording methods and reporting are specified, to promote consistency of methods for diagnosis, monitoring and inter-laboratory comparisons, while also responding to evolving clinical practices and technology. The main changes in this updated ISCEV Standard for clinical ERGs include specifying that ERGs may meet the Standard without mydriasis, providing stimuli adequately compensate for non-dilated pupils. There is more detail about analysis of dark-adapted oscillatory potentials (OPs) and the document format has been updated and supplementary content reduced. There is a more detailed review of the origins of the major ERG components. Several tests previously tabulated as additional ERG protocols are now cited as published ISCEV extended protocols. A non-standard abbreviated ERG protocol is described, for use when patient age, compliance or other circumstances preclude ISCEV Standard ERG testing.

Clinical electrophysiological testing of the visual system incorporates a range of noninvasive tests and provides an objective indication of function relating to different locations and cell types within the visual system. This document developed by the International Society for Clinical Electrophysiology of Vision provides an introduction to standard visual electrodiagnostic procedures in widespread use including the full-field electroretinogram (ERG), the pattern electroretinogram (pattern ERG or PERG), the multifocal electroretinogram (multifocal ERG or mfERG), the electrooculogram (EOG) and the cortical-derived visual evoked potential (VEP). The guideline outlines the basic principles of testing. Common clinical presentations and symptoms are described with illustrative examples and suggested investigation strategies.

The multifocal electroretinogram (mfERG) is an electrophysiological test that allows the function of multiple discrete areas of the retina to be tested simultaneously. This document, from the International Society for Clinical Electrophysiology of Vision (ISCEV), presents an updated and revised ISCEV standard for clinical mfERG and defines minimum protocols for basic clinical mfERG recording and reporting so that responses can be recognized and compared from different laboratories worldwide. The major changes compared with the previous mfERG standard relate to the minimum length of m-sequences used for recording, reporting of results and a change in document format, to be more consistent with other ISCEV standards.

The stretching of a myopic eye is associated with several structural and functional changes in the retina and posterior segment of the eye. Recent research highlights the role of retinal signaling in ocular growth. Evidence from studies conducted on animal models and humans suggests that visual mechanisms regulating refractive development are primarily localized at the retina and that the visual signals from the retinal periphery are also critical for visually guided eye growth. Therefore, it is important to study the structural and functional changes in the retina in relation to refractive errors. This review will specifically focus on electroretinogram (ERG) changes in myopia and their implications in understanding the nature of retinal functioning in myopic eyes. Based on the available literature, we will discuss the fundamentals of retinal neurophysiology in the regulation of vision-dependent ocular growth, findings from various studies that investigated global and localized retinal functions in myopia using various types of ERGs.

Currently, electroretinograms (ERGs) are mainly recorded while using flashes as stimuli. In this review, we will argue that strong flashes are not ideal for studying visual information processing. ERG responses to periodic stimuli may be more strongly associated with the activity of post-receptoral neurons (belonging to different retino-geniculate pathways) and, therefore, be more relevant for visual perception. We will also argue that the use of periodic stimuli may be an attractive addition to clinically available retinal electrophysiological methods.

The International Society for Clinical Electrophysiology of Vision (ISCEV) Standard for full-field electroretinography (ERG) describes a minimum procedure, but encourages more extensive testing. This ISCEV extended protocol describes an extension to the ERG Standard, namely the photopic negative response (PhNR) of the light-adapted flash ERG, as a well-established technique that is broadly accepted by experts in the field. The PhNR is a slow negative-going wave after the b-wave that provides information about the function of retinal ganglion cells and their axons. The PhNR can be reduced in disorders that affect the innermost retina, including glaucoma and other forms of optic neuropathy. This document, based on existing literature, provides a protocol for recording and analyzing the PhNR in response to a brief flash. The protocol includes full-field stimulation, a frequency bandwidth of the recording in which the lower limit does not exceed 0.3 Hz, and a spectrally narrowband stimulus, specifically, a red flash on a rod saturating blue background. Suggested flash strengths cover a range up to and including the minimum required to elicit a maximum amplitude PhNR. This extended protocol for recording the PhNR provides a simple test of generalized retinal ganglion cell function that could be added to standard ERG testing.

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.

The electroretinogram (ERG) measures the electrical activity of retinal neurons and glial cells in response to a light stimulus. Amongst other techniques, clinicians utilize the ERG to diagnose various eye diseases, including inherited conditions such as cone-rod dystrophy, rod-cone dystrophy, retinitis pigmentosa and Usher syndrome, and to assess overall retinal health. An ERG measures the scotopic and photopic systems separately and mainly consists of an a-wave and a b-wave. The other major components of the dark-adapted ERG response include the oscillatory potentials, c-wave, and d-wave. The dark-adapted a-wave is the initial corneal negative wave that arises from the outer segments of the rod and cone photoreceptors hyperpolarizing in response to a light stimulus. This is followed by the slower, positive, and prolonged b-wave, whose origins remain elusive. Despite a large body of work, there remains controversy around the mechanisms involved in the generation of the b-wave. Several hypotheses attribute the origins of the b-wave to bipolar or Müller glial cells or a dual contribution from both cell types. This review will discuss the current hypothesis for the cellular origins of the dark-adapted ERG, with a focus on the b-wave.

Background To evaluate the electroretinogram waveform in autism spectrum disorder and attention deficit hyperactivity disorder using a discrete wavelet transform (DWT) approach. Methods A total of 55 autism spectrum disorder (ASD), 15 attention deficit hyperactivity disorder (ADHD) and 156 control individuals took part in this study. Full field light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, accounting for pupil size, with five flash strengths ranging from -0.12 to 1.20 log photopic cd.s.m-2. A DWT analysis was performed using the Haar wavelet on the waveforms to examine the energy within the time windows of the a- and b-waves and the oscillatory potentials (OPs) which yielded six DWT coefficients related to these parameters. The central frequency bands were from 20-160 Hz relating to the a-wave, b-wave and OPs represented by the coefficients: a20, a40, b20, b40, op80 and op160 respectively. In addition, the b-wave amplitude and percentage energy contribution of the OPs (%OPs) in the total ERG broadband energy was evaluated. Results There were significant group differences (p<.001) in the coefficients corresponding to energies in the b-wave (b20, b40) and OPs (op80 and op160) as well as the b-wave amplitude. Notable differences between the ADHD and control groups were found in the b20 and b40 coefficients. In contrast, the greatest differences between the ASD and control group were found in the op80 and op160 coefficients. The b-wave amplitude showed both ASD and ADHD significant group differences from the control participants, for flash strengths greater than 0.4 log photopic cd.s.m-2 (p<.001). Conclusions This methodological approach may provide insights about neuronal activity in studies investigating group differences where retinal signaling may be altered through neurodevelopment or neurodegenerative conditions. However, further work will be required to determine if retinal signal analysis can offer a classification model for neurodevelopmental conditions in which there is a co-occurrence such as ASD and ADHD,

Purpose Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are conditions that similarly alter cognitive functioning ability and challenge the social interaction, attention, and communication skills of affected individuals. Yet these are distinct neurological conditions that can exhibit diverse characteristics which require different management strategies. It is desirable to develop tools to assist with early distinction so that appropriate early interventions and support may be tailored to an individual’s specific requirements. The current diagnostic procedures for ASD and ADHD require a multidisciplinary approach and can be lengthy. This study investigated the potential of electroretinogram (ERG), an eye test measuring retinal responses to light, for rapid screening of ASD and ADHD. Methods: Previous studies identified differences in ERG amplitude between ASD and ADHD, but this study explored time-frequency analysis (TFS) to capture dynamic changes in the signal. ERG data from 286 subjects (146 control, 94 ASD, 46 ADHD) was analyzed using two TFS techniques. Results: Key features were selected, and machine learning models were trained to classify individuals based on their ERG response. The best model achieved 70% overall accuracy in distinguishing control, ASD, and ADHD groups. Conclusion: The ERG to the stronger flash strength provided better separation and the high frequency dynamics (80–300 Hz) were more informative features than lower frequency components. To further improve classification a greater number of different flash strengths may be required along with a discrimination comparison to participants who meet both ASD and ADHD classifications and carry both diagnoses.